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<body bgcolor="white" lang="EN-US" link="blue" vlink="purple" style="tab-interval:36.0pt" alink="fushia">

<div class="WordSection1">

<h1 align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext">ICAOR 2010 ABSTRACTS<o:p></o:p></span></h1>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b style="mso-bidi-font-weight:normal"><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext;mso-no-proof:yes">2<sup>ND</sup> I</span></b><b style="mso-bidi-font-weight:normal"><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext">NTERNATIONAL CONFERENCE ON APPLIED
OPERATIONAL RESEARCH<o:p></o:p></span></b></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b style="mso-bidi-font-weight:normal"><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext">25-27 AUGUST 2010, TURKU, FINLAND<o:p></o:p></span></b></p>

<div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">OPTIMIZATION OF DAILY SCHEDULING FOR EXTRAMURAL HEALTH CARE
SERVICES </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Andrea
Trautsamwieser and Patrick Hirsch <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Institute
of Production and Logistics University of Natural Resources and Applied Life
Sciences Vienna, Austria <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext;mso-bidi-font-weight:normal">Abstract.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal;mso-bidi-font-weight:bold"> As demographic trends show, the
demand for home health care services will rise in future. Currently, the
routing of the nurses is performed manually by the main service providers in
Austria. This leads to a time-consuming process with a presumably suboptimal
outcome. This paper presents a model formulation and a metaheuristic solution
approach, based on Variable Neighbourhood Search, for optimizing the daily
scheduling of the nurses. The objective is to minimize the time spent by the
nurses for travelling including driving and waiting. Additionally, the
dissatisfaction level of nurses and clients is minimized. A feasible solution
has to observe working time regulations, hard time windows, mandatory breaks, and
a feasible assignment of nurses to clients. The proposed method finds the
global optimal solutions for small problem instances. In extensive numerical
studies it is shown that the algorithm is capable to solve real life instances
with up to 512 home visits and 75 nurses.</span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext;font-weight:normal"><o:p></o:p></span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">AUTOMATED MULTI-SKILL SHIFT DESIGN FOR HOSPITALS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Eivind
J. Nilssen, Martin Stølevik, Erik Lien Johnsen and Tomas Eric Nordlander <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">SINTEF
ICT, Department of Applied Mathematics Oslo, Norway <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
For labour intensive organizations, finding a good match between the predicted
workload and the scheduled workforce work capacity is crucial: One important
step in this matching process is shift design. In a multi-skill shift design
problem, the model must reflect the skill attributes of the employees and the time
dependent demand of each skill type. For hospitals, a number of constraints and
objectives complicate the picture, and in this paper we introduce models which
reflect many of the challenges faced by planners at two reference hospitals in
Norway. Experiments using mixed-integer programming solvers show promising
results, and optimal solutions are in some cases found within seconds or a few
minutes. <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A TWO-PHASE APPROACH FOR THE OPERATING ROOM PLANNING AND
SCHEDULING PROBLEM </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">John
Fowler and Qing Li <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Arizona
State University Tempe, AZ, USA <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Hospitals nowadays face an increasing pressure for efficient resource usage
while providing timely patient care. Planning and scheduling the Operating
Room, which is one of the largest cost unit, is thus important and has
attracted the attention of many researchers. In this paper, we develop a two
phase approach for cyclic block scheduling of OR (Phase 1) and day-to-day
patient scheduling (Phase 2). Each phase is formulated as a mixed integer
program and exact solutions are obtained using real data. Random Keys Genetic
Algorithm is used in the second phase and compared with optimal solutions. <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">FIVE SECTIONS ANALYSIS: THE OR/MS PROCESS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Heiner
Müller-Merbach <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Technische
Universität Kaiserslautern Wirtschaftsinformatik und Operations Research
Germany <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
A five section analysis is suggested for the OR/MS process. The author’s first
(German) publication on this topic leads back to 1987 (Müller-Merbach, 1987),
the first English publication to 2010 (Müller-Merbach, 2010). In this paper,
OR/MS shall be understood according to an officious definition of OR by the
Operations Research Society of America (ORSA, 1977) (i. e. prior to the merger
of ORSA and TIMS to INFORMS by January 1, 1995), such as: “Operations Research
is concerned with scientifically deciding how to best design and operate
man-machine systems, usually under conditions requiring the allocation of
scarce resources.” In this definition: (i) “mathematics” is not explicitly
mentioned, (ii) “scientifically deciding” is to be interpreted as
“interdisciplinary”, i. e. including all the relevant knowledge available,
(iii) “how to best design and operate”, i. e. aiming at optimality of the
structures and the processes, (iv) “man-machine systems”, i. e. combined social
and technical systems, such as enterprises, political states/nations,
universities, hospitals, political parties etc. and their sections.<o:p></o:p></span></p>

<div>

<div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></div>

</div>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">METAHEURISTICS
FOR THE WASTE COLLECTION VEHICLE ROUTING PROBLEM WITH TIME WINDOWS <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">AM
Benjamin and JE Beasley <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Brunel
University Uxbridge, UK <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext;mso-bidi-font-weight:normal">Abstract.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal;mso-bidi-font-weight:bold"> In this problem there is a set
of customers which waste is collected by vehicles. Vehicles can visit waste
disposal facilities during their working day to empty collected waste and hence
continue to collect from customers. The vehicles start and end their routes at
a single depot empty. We take into consideration time windows associated with
customers, disposal facilities and the depot. Here, we also have a driver rest
period. The problem is solved using a number of metaheuristic algorithms namely
tabu search (TS) and variable neighbourhood search (VNS). Moreover, we also
present a combined metaheuristic algorithm based on variable neighbourhood tabu
search (VNTS), where the variable neighbourhood is searched via tabu search.
Computational experiments on ten publicly available waste collection benchmark
problems involving up to 2092 customers and 19 waste disposal facilities
indicates that the proposed algorithms are able to find better quality
solutions than previous work presented in literature within reasonable
computation times.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal"><o:p></o:p></span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

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<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">THE SOFTWARE SUPPORT FOR MULTIPLE-CRITERIA EVALUATION –
VARIOUS TYPES OF PARTIAL EVALUATIONS AGGREGATION </span><span style="font-size:
9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Pavel
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椀氀礀㨀਀䄀爀椀愀氀㬀挀漀氀漀爀㨀眀椀渀搀漀眀琀攀砀琀∀㸀਀਀㰀栀爀 猀椀稀攀㴀∀㈀∀ 眀椀搀琀栀㴀∀㄀　　─∀ 渀漀猀栀愀搀攀 猀琀礀氀攀㴀∀挀漀氀漀爀㨀⌀䄀　䄀　䄀　∀ 愀氀椀最渀㴀∀氀攀昀琀∀㸀਀਀㰀⼀猀瀀愀渀㸀㰀⼀栀㈀㸀਀਀㰀栀㈀ 愀氀椀最渀㴀∀氀攀昀琀∀ 猀琀礀氀攀㴀∀洀愀爀最椀渀㨀　挀洀㬀洀愀爀最椀渀ⴀ戀漀琀琀漀洀㨀⸀　　　㄀瀀琀㬀琀攀砀琀ⴀ愀氀椀最渀㨀氀攀昀琀㬀਀氀椀渀攀ⴀ栀攀椀最栀琀㨀渀漀爀洀愀氀∀㸀㰀猀瀀愀渀 猀琀礀氀攀㴀∀昀漀渀琀ⴀ猀椀稀攀㨀㤀⸀　瀀琀㬀昀漀渀琀ⴀ昀愀洀椀氀礀㨀☀焀甀漀琀㬀䌀愀洀戀爀椀愀☀焀甀漀琀㬀Ⰰ☀焀甀漀琀㬀猀攀爀椀昀☀焀甀漀琀㬀㬀਀洀猀漀ⴀ愀猀挀椀椀ⴀ琀栀攀洀攀ⴀ昀漀渀琀㨀洀愀樀漀爀ⴀ氀愀琀椀渀㬀洀猀漀ⴀ昀愀爀攀愀猀琀ⴀ昀漀渀琀ⴀ昀愀洀椀氀礀㨀☀焀甀漀琀㬀吀椀洀攀猀 一攀眀 刀漀洀愀渀☀焀甀漀琀㬀㬀਀洀猀漀ⴀ栀愀渀猀椀ⴀ琀栀攀洀攀ⴀ昀漀渀琀㨀洀愀樀漀爀ⴀ氀愀琀椀渀㬀洀猀漀ⴀ戀椀搀椀ⴀ昀漀渀琀ⴀ昀愀洀椀氀礀㨀䄀爀椀愀氀㬀挀漀氀漀爀㨀眀椀渀搀漀眀琀攀砀琀㬀਀昀漀渀琀ⴀ眀攀椀最栀琀㨀渀漀爀洀愀氀∀㸀䤀一吀䔀刀䄀䌀吀䤀伀一匀 䄀䴀伀一䜀 䌀刀䤀吀䔀刀䤀䄀 䄀匀 䴀伀䐀䔀䰀䰀䔀䐀 䈀夀 䘀唀娀娀䤀䘀䤀䔀䐀਀䌀䠀伀儀唀䔀吀 䤀一吀䔀䜀刀䄀䰀 㰀⼀猀瀀愀渀㸀㰀猀瀀愀渀 猀琀礀氀攀㴀∀昀漀渀琀ⴀ猀椀稀攀㨀㤀⸀　瀀琀㬀昀漀渀琀ⴀ昀愀洀椀氀礀㨀☀焀甀漀琀㬀䌀愀洀戀爀椀愀☀焀甀漀琀㬀Ⰰ☀焀甀漀琀㬀猀攀爀椀昀☀焀甀漀琀㬀㬀਀洀猀漀ⴀ愀猀挀椀椀ⴀ琀栀攀洀攀ⴀ昀漀渀琀㨀洀愀樀漀爀ⴀ氀愀琀椀渀㬀洀猀漀ⴀ昀愀爀攀愀猀琀ⴀ昀漀渀琀ⴀ昀愀洀椀氀礀㨀☀焀甀漀琀㬀吀椀洀攀猀 一攀眀 刀漀洀愀渀☀焀甀漀琀㬀㬀਀洀猀漀ⴀ栀愀渀猀椀ⴀ琀栀攀洀攀ⴀ昀漀渀琀㨀洀愀樀漀爀ⴀ氀愀琀椀渀㬀洀猀漀ⴀ戀椀搀椀ⴀ昀漀渀琀ⴀ昀愀洀椀氀礀㨀䄀爀椀愀氀㬀挀漀氀漀爀㨀眀椀渀搀漀眀琀攀砀琀∀㸀㰀漀㨀瀀㸀㰀⼀漀㨀瀀㸀㰀⼀猀瀀愀渀㸀㰀⼀栀㈀㸀਀਀㰀瀀 愀氀椀最渀㴀∀氀攀昀琀∀ 猀琀礀氀攀㴀∀洀愀爀最椀渀ⴀ戀漀琀琀漀洀㨀　挀洀㬀洀愀爀最椀渀ⴀ戀漀琀琀漀洀㨀⸀　　　㄀瀀琀㬀琀攀砀琀ⴀ愀氀椀最渀㨀氀攀昀琀∀㸀㰀猀瀀愀渀 猀琀礀氀攀㴀∀昀漀渀琀ⴀ猀椀稀攀㨀㤀⸀　瀀琀㬀昀漀渀琀ⴀ昀愀洀椀氀礀㨀☀焀甀漀琀㬀䌀愀洀戀爀椀愀☀焀甀漀琀㬀Ⰰ☀焀甀漀琀㬀猀攀爀椀昀☀焀甀漀琀㬀㬀洀猀漀ⴀ愀猀挀椀椀ⴀ琀栀攀洀攀ⴀ昀漀渀琀㨀洀愀樀漀爀ⴀ氀愀琀椀渀㬀਀洀猀漀ⴀ栀愀渀猀椀ⴀ琀栀攀洀攀ⴀ昀漀渀琀㨀洀愀樀漀爀ⴀ氀愀琀椀渀㬀洀猀漀ⴀ戀椀搀椀ⴀ昀漀渀琀ⴀ昀愀洀椀氀礀㨀䄀爀椀愀氀㬀挀漀氀漀爀㨀眀椀渀搀漀眀琀攀砀琀∀㸀䤀瘀攀琀愀਀䈀攀戀Āáková and Jana Talašová <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Palacký
University Olomouc Olomouc, Czech Republic <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Within evaluation models, the integrand of the discrete Choquet integral
represents partial evaluations of an alternative with respect to given
criteria, while the fuzzy measure, i.e. the generalised monotonic measure,
stands for the weights of the sets of criteria. We focus on fuzzified Choquet
integral. We study the first-level fuzzified Choquet integral that handles partial
fuzzy evaluations. Then we employ the second-level fuzzified Choquet integral
where also the weights of the sets of criteria are in the form of fuzzy
numbers. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">THE REPRESENTATION OF UNCERTAINTY IN OPERATIONAL RESEARCH:
CONSIDERATIONS ON THE USE OF POSSIBILITY, PROBABILITY, AND FUZZY NUMBERS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Matteo
Brunelli and Mario Fedrizzi<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">IAMSR
and Turku Centre for Computer Science Åbo Akademi University Turku, Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Ttrento Trento, Italy <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">The judgment of the reliability, credibility, or
adequacy of the available information plays a critical role when one or more
individuals have to make decisions in the presence of uncertainty. In decision
making activities, most of the uncertainty comes from subjective judgments and
is commonly transmitted through statements in natural language involving vague
predicates and therefore linguistic uncertainty is generated, i.e., the
uncertainty about a precisely defined quantity that is produced by linguistic
information. In this paper we discuss some issues in the application of
possibility and probability theory in the domain of operational research. In
doing so, we emphasize how, sometimes, justifications for the use of fuzzy
numbers in the representation of uncertainty, lack formality or empirical
background. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">EXPERIMENTS TO IMPROVE FORECASTING ACCURACY OF REGRESSION
MODELS WITH MINIMAL ASSUMPTIONS </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Magderie
van der Westhuizen, Giel Hattingh and Hennie Kruger <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">North-West
University, South Africa <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The forecasting accuracy of a regression model relies heavily on the
applicability of the assumptions made by the model builder. In addition, the
presence of outliers may also lead to models that are not reliable and thus
less robust. In this paper a suggested regression model, based on minimal
assumptions, is studied and extended in an effort to improve forecast accuracy.
The approach is based on mathematical programming techniques combined with
smoothing and piecewise linear techniques. Three cases from the literature are
considered and presented as illustrative examples. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">HYBRID GENETIC PATTERN SEARCH AUGMENTED LAGRANGIAN
ALGORITHM: APPLICATION TO WWTP OPTIMIZATION </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Isabel
A.C.P. Espirito Santo, Lino Costa, Roman Denysiuk and Edite MGP Fernandes<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Minho, Campus de Gualtar, Braga, Portugal <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Algoritmi
R&amp;D Center, Portugal <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
An augmented Lagrangian algorithm is presented to solve a global optimization
problem that arises when modeling the activated sludge system in a Wastewater
Treatment Plant, attempting to minimize both investment and operation costs. It
is a heuristic-based algorithm that uses a genetic algorithm to explore the
search space for a global optimum and a pattern search method for the local
search refinement. The obtained results have physical meaning and show the
effectiveness of the proposed method. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">WHICH RATING AGENCY ACHIEVED RATING STABILITY, MOODY’S AND
R&amp;I? EMPIRICAL STUDY USING AN ARTIFICIAL NEURAL NETWORK </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Motohiro
Hagiwara, Katsuaki Tanaka, Hideki Katsuda and Susumu Saitou<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Meiji
University Japan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Setsunan
University Japan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Kinki
University Japan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Sophia
Universities Japan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">The distribution of ratings changes plays a crucial
role in many credit risk models. As is well-known, these distributions vary
across time and different issuer types. Ignoring such dependencies may lead to
inaccurate assessments of credit risk. We introduce a new approach to improve
the performance of rating prediction models for multinational corporations. In
the last decade, neural networks have emerged from an esoteric instrument in
academic research to a rather common tool assisting auditors, investors,
portfolio managers and investment advisors in making critical financial
decisions. It is apparent that a better understanding of the network's
performance and limitations would help both researchers and practitioners in
analysing real-world problems. The objectives of this research is to verify the
effectiveness of artificial neural networks (ANNs) and examine and compare the
stability of rating structures of rating agencies in the United States and
Japan. Method to predict corporate ratings by public quantitative information
in an inter-temporally stable manner would be useful from the perspective of
cost-benefit performance especially in recent rapidly changing economic
situation. We find that ANNs has more explanatory power in many cases than
models by previous research and that R&amp;I and Moody’s changed rating
structure significantly in 2006 and 2007 respectively. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A FLEXIBLE FORECASTING INTELLIGENT MODEL FOR NON-STATIONARY
TIME SERIES </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Iulian
Nastac <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Politehnica
University of Bucharest Bucharest, Romania <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The paper presents a general adaptive model for those dynamic systems that work
on continuously changing environments. This interdisciplinary model is tested
in the financial, genetic and technical fields. The algorithm of the model
establishes how a viable structure of an artificial neural network at a
previous moment of time could be retrained in an efficient manner, in order to
support modifications in a complex input output function of a real forecasting
system. A “remembering process” from the previous learning phase is used to
enhance the accuracy of the predictions. The advantage of the retraining
procedure is that some relevant aspects are preserved not only from the
immediate previous training phase, but also from the previous but one phase,
and so on. A kind of “slow forgetting process” also occurs; thus it is much
easier for the model to remember specific aspects of the previous training
instead of an oldest one. <o:p></o:p></span></p>

<div>

<div class="MsoNormal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></div>

</div>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A COMPUTATIONALLY INEXPENSIVE APPROACH IN MULTI-OBJECTIVE
HEAT EXCHANGER NETWORK SYNTHESIS </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Markus
Hartikainen and Kaisa Miettinen <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Jyväskylä Jyväskylä, Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
We consider a heat exchanger network synthesis problem formulated as a
multi-objective optimization problem. The Pareto front of this problem is
approximated with a new approximation approach and the preferred point on the
approximation is found with the interactive multi-objective optimization method
NIMBUS. Using the approximation makes the solution process computationally
inexpensive. Finally, the preferred outcome on the Pareto front approximation
is projected on the actual Pareto front. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">ANALYZING COST STRUCTURES OF INVENTORY ROUTING: APPLICATION
TO CASH SUPPLY CHAINS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Michael
Wagner <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Hanken
School of Economics Helsinki, Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This paper analyzes cost structures of inventory routing and investigates
efficiency gains that result from combining vehicle routing and inventory
management. Mixed-integer models are applied to determine the optimal
replenishment schedule. Total costs of a sequential approach are contrasted
with an integrated approach in order to capture the impact of the underlying
set-dependent cost structure. The proposed methodology applies simulation and a
factorial design to analyze the role of set-dependent cost structures as well
as the impact of demand, cost factors, factor levels and interaction effects.
Cost benefits are evaluated in a deterministic environment using nominal range
sensitivity analysis and repeated measure analysis of variance (ANOVA). The
approach is illustrated for a local network of Automated Teller Machines (ATMs)
using empirical data of an international commercial bank. Results of the case
study show that cost benefits of the integrated approach vary with factor
levels and are primarily determined by routing costs with remaining factors
having only limited impact. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">SOLVING A COMPLEX PRODUCTION PLANNING PROBLEM WITH
MATHEMATICAL PROGRAMMING TECHNIQUES </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Mikael
Nyberg and Kaj-Mikael Björk <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Åbo
Akademi University Turku, Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This paper presents a new MILP (Mixed Integer Linear Programming) model to
solve a complex production planning problem. The problem is found in a producer
of food sweeteners, with several different kinds of products. The case study
plant is found in the USA. The process is fairly complex and the alternatives
are vast. A discrete-time production planning model is presented and found
suitable for the solution of the problem as well as a discussion how to reduce
complexity in large processes without loosing good solutions. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">NURSE ROSTERING IN A DANISH HOSPITAL </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Jonas
Bæklund <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Aarhus
University Aarhus, Denmark <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Nurse rostering is the complex scheduling problem of planning which shift each
nurse should work for the next period. The problem confronted is a nurse
rostering problem in a ward at a Danish hospital; the problem includes several
special regulations that have to be fulfilled in this ward. This presentation
will present the first results of the on-going work of my Ph.D. thesis project.
It gives moreover an overview on the solution approach we are currently working
on. The overall method is a branch and price algorithm based on a linear master
problem and a sub-problem handled with heuristics and constraint programming. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">MODELLING TO GENERATE ALTERNATIVE POLICIES IN HIGHLY
UNCERTAIN ENVIRONMENTS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Julian
Scott Yeomans <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Schulich
School of Business York University Toronto, ON, Canada <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">Public policy formulation often proves to be an
extremely complicated endeavour due to the considerable uncertainty within its
various system components. The complexity of public sector decision-making is
further compounded by competing performance design objectives and requirements
that are difficult to specify, quantify and capture at the time ancillary
decision models are constructed. Consequently, there are invariably unmodelled
performance design issues, not apparent at the time of model construction, which
can greatly impact the acceptability of its solutions. In particular, while a
mathematically optimal solution may prove to be the best solution for the
modelled problem, it is frequently not the best solution to the real problem.
Therefore, in public policy formulation, it is generally preferable to create
several quantifiably good alternatives that provide very different structural
approaches and perspectives to the problem – an approach referred to as
“modelling to generate alternatives”. The potentially unique performance
features within these dissimilar alternatives are expected to result in them
performing very differently with respect to the unmodeled issues, thus
providing a means for capturing and incorporating the unmodelled issues into
the solution process. This presentation reviews recent research in modelling to
generate alternatives and shows how it can be used to generate numerous policy
alternatives that satisfy required system performance criteria in highly
uncertain environments and yet are maximally different in the decision space.
Many of these techniques can be adapted to a wide variety of problem types and
can be extended into many different types of operational and strategic planning
applications. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A REAL TIME QUALITY DECISION SUPPORT MODEL FOR THE
CONSTRUCTION INDUSTRY </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Marios
Charalambides, Michalis Menicou, Petros Christou and Vassos Vassiliou <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Frederick
University Nicosia, Cyprus <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Construction Industry across the Globe is at a crossroad striving for its
survival after the recent economic crisis. Issues relating to product quality
and cost minimization prove to be of the outmost importance for the sector’s
successful future. Within this context, this paper presents a real time
quality-cost optimization model for the construction industry, applied to the
residential housing sector. The model is based on a quality assurance tool,
accompanied by the necessary methodology to identify the optimum path of
improvements to be made in order to restore the desired quality of construction
with the minimum cost. A prototype optimization tool is also presented. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">ASSESSING ACADEMIC STAFF PERFORMANCE USING MULTIPLE
CRITERIA EVALUATION MODELS </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Jana
Talašová and Jan Stoklasa <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Palacký
University Olomouc Olomouc, Czech Republic <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Various academic staff evaluation models were subjected to detailed analysis.
The routine use of weighted mean as a sole aggregation operator proved
inappropriate for aggregating evaluations from different academic areas
(lecturing, R&amp;D, management). Even more general aggregation operators (OWA,
WOWA) still leave some room for improvement. To objectively assess benefit of
an individual staff member, the use of a fuzzy rule base in aggregating partial
evaluations proves optimal. Our proposed linguistic fuzzy evaluation model is
currently being implemented at Palacky University Olomouc. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">OPTIPROT – A SPREADSHEET-BASED DECISION SUPPORT SYSTEM FOR
BLENDING PROBLEMS IN FOOD-PROCESSING COMPANY </span><span style="font-size:
9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Veronika
Skocdopolova and Josef Jablonsky <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Economics Prague, Czech Republic <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The paper presents the model for production process optimisation in large
international milk processing company. The model is used in OPTIPROT
application which was created for this company and is used for operational
planning. The application optimises production process of so called white
masses and purchase of raw milk and other milk ingredients. Optimization
criterion of the model is minimisation of total production costs. This problem
was formulated as a standard blending problem with many specific features.
OPTIPROT application uses MS Excel interface written in VBA (Visual Basic for
Application) co-operating with optimisation system LINGO. Optimal results offer
recommendation for purchase of raw materials, own production of materials,
surplus sales of raw materials, and stock creating. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A CO-EVOLUTIONARY SIMULATION-OPTIMIZATION ALGORITHM FOR
MODELLING TO GENERATE ALTERNATIVES IN MUNICIPAL SOLID WASTE MANAGEMENT PLANNING
</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:
major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:
major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Julian
Scott Yeomans and Yavuz Gunalay<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Schulich
School of Business York University Toronto, ON, Canada. <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Bahcesehir
University Istanbul, Turkey <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Public sector decision-making typically involves complex problems that are
riddled with competing performance objectives and possess design requirements
which are difficult to quantify and capture at the time decision models are
constructed. Environmental policy formulation can prove additionally
complicated because the various system components often contain considerable
stochastic uncertainty and frequently there are also numerous stakeholders
holding incompatible perspectives. Consequently, there are invariably
unmodelled performance design issues, not apparent at the time of the problem
formulation, which can greatly impact the acceptability of any proposed
solutions. While a mathematically optimal solution might provide the best
solution to a modelled problem, normally this will not be the best solution to
the real problem. Therefore, in public environmental policy formulation, it is
generally preferable to be able to create several quantifiably good
alternatives that provide very different approaches and perspectives to the
problem. This study shows how simulation-optimization (SO) modelling can be
combined into a co-evolutionary algorithm to efficiently generate multiple
policy alternatives that satisfy required system performance criteria in highly
uncertain environments and yet are maximally different in the decision space.
The efficacy of this modelling-to-generate alternatives approach is
specifically demonstrated on a municipal solid waste management planning case. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">HYBRIDISATIONS OF HARMONY SEARCH ALGORITHM WITH BANDWIDTH
AND VARIABLE NEIGHBOURHOOD SEARCH ELEMENTS FOR NOISY RESPONSE SURFACE
OPTIMISATIONS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Pongchanun
Luangpaiboon <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Thammasat
University Pathumthani, Thailand <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
A response surface supposes the yield of an engineering system depends on a
number of influential variables, which are restricted to some region of safe
operation. The expected value of response is some unknown function of
influential variables, and the measured yields will vary about their expected
values because of random errors. These errors are comprised of natural
variation in the process and measurement errors, which occur when monitoring
the yield, and are assumed to have a mean of zero and to be uncorrelated with
the values taken by influential variables. Errors in measuring the values of
the k influential variables are usually assumed to be negligible in comparison
with the random errors associated with the yield. In this paper we examine
variations of a harmony search algorithm (HSA) based on bandwidth and variable
neighbourhood search elements, for different error standard deviations. All the
algorithms are run until they converge. The requirements are that an algorithm
converges to the optimum, and that it does so as quickly as possible. The
objective of this paper is to investigate how the choice of best algorithm for
optimisation depends on the amount of random variation in process yields when
parameters are fixed. The results show that the HSA with the variable
neighbourhood search elements seems to be better in terms of the mean and
variance of design points and yields. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">AN ALGORITHM TO FIND THE BEST APPROXIMATE SOLUTIONS FOR A
PARTICULAR FUZZY RELATIONAL EQUATION WITH MAX-PRODUCT COMPOSITION </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Yan-Kuen
Wu and Cheng-Chuang Hon<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Vanung
University Taoyuan, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Minghsin
University of Science and Technology Xinfeng Hsinchu, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Fuzzy relational equations have played an important role in fuzzy modelling and
have applied to many practical problems. Most theoretical results of fuzzy
relational equations based on a premise that the solution set is nonempty.
However, it is commonly seen that the case of fuzzy relational equations is
inconsistent. The inconsistent fuzzy relational equation is so-called “inverse
fuzzy relation” problem. Finding the approximate solution for inverse fuzzy
relation problem has been investigated by several authors. The proposed
algorithm for solving the inverse fuzzy relation problem usually based on the
genetic algorithm (GA) or heuristic algorithm. However, these algorithms are
expected to yield good results in most cases but are not guaranteed to yield
the best approximate solution. To provide a precisely solution procedure, an
algorithm to find the best approximate solution of the inverse fuzzy relation
problem included the right hand side vector <span style="mso-bidi-font-style:
italic">b</span> = (1 0 … 0) with max-product composition is presented in this
study. Numerical examples are also provided to illustrate how the solution
algorithm can be applied to find the best approximate solution for the studied
problem. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">EFFICIENCY EVALUATION OF HYDROELECTRIC POWER PLANTS USING
DATA ENVELOPMENT ANALYSIS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">V
Dedoussis, K Konstas, A Kassimis and S Sofianopoulou <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Piraeus Piraeus, Greece <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The purpose of this paper is to evaluate the efficiency of a network of
hydroelectric power plants using the Data Envelopment Analysis approach. The
network is modelled as a linear system with multiple inputs and outputs. As
inputs one could consider, for instance, the age of a plant, the total number
of hours that a plant is in operation during each year, etc. As outputs the
model considers the electrical energy delivered per year, the number of hours
that the plant is not in operation, etc. The proposed approach does not only
evaluate each plant relative to the other ones, but it also ‘produces’ policy
making scenarios that would enable plant managers to improve the plant’s
operational characteristics. Computational results based on real-world data are
presented and discussed. Relationships between efficiency scores and various
inputs/outputs are also investigated and some interesting trends are
identified. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">AN EXTENDED CASE-BASED DISTANCE APPROACH FOR ALTERNATIVES
SCREENING </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Li-Ching
Ma and Pei-Pei Hsu<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">National
United University MiaoLi City, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">I-Shou
University Kaohsiung County, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Screening is a helpful process to reduce larger set of alternatives into a
smaller set that contains the best alternatives, thus decision makers can
concentrate on evaluating alternatives in the smaller set. Hence, how to assist
decision makers in screening out poor alternatives is an important issue in
multiple criteria decision making. This study tries to develop a screening
model incorporating the advantages of the case-based distance method and the
discriminate analysis. From the concept of the case-based distance method, the
proposed approach can obtain criterion weights and screening rules by eliciting
decision makers’ preferences based on a set of test cases. Moreover, the
proposed approach can increase hit rates and improve multiple solution problems
of conventional cased-based distance methods. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">BI-CRITERIA HEURISTIC FOR SCHEDULING ON UNRELATED PARALLEL
MACHINES </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">YK
Lin, JW Fowler and ME Pfund<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Feng
Chia University Taichung, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Arizona
State University Tempe, AZ, USA <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
In this research, a bi-criteria heuristic is proposed to find non-dominated
solutions to the unrelated parallel machines scheduling problem that minimizes
makespan and total weighted tardiness. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A MIXED INTEGER PROGRAMMING FORMULATION FOR PARALLEL
MACHINES SCHEDULING WITH A SINGLE SERVER </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Mi-Yi
Kim and Young Hoon Lee <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Yonsei
University Seoul, Korea <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This paper considers the identical parallel machines scheduling problem (PMSP)
with a single server, which is in charge of job setups. A job can be processed
with a precedent setup by a server on one of the machines. The setup can be
processed at only one machine at any time because of the single server
constraint. In this paper, the Problem P,S1|<span style="mso-bidi-font-style:
italic">sj</span>|<span style="mso-bidi-font-style:italic">C</span>max with a
general job set is formulated in a mixed integer programming, which is
developed by taking the characteristic of the single server problem into
account and modifying the description of server waiting time identified by
Adbekhodaee and Wirth(2002). <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A GENETIC ALGORITHM FOR DISTRIBUTED SCHEDULING IN SUPPLY
NETWORKS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Anna
Ławrynowicz <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Warsaw
School of Economics Warszawa, Poland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> In
this paper, the author proposes a genetic algorithm for a distributed
scheduling in supply networks. The new genetic algorithm enables not only a
manufacturing scheduling. Additionally, the genetic algorithm aided planners in
transport orders planning. The algorithm is based on operation codes, where
each chromosome is a set of 5-position genes. The new method was verification
in some experiments. Finally, representative examples are illustrated to
indicate that the suggested new method can improve distributed scheduling in
supply networks. It can be applied in a dynamic setting when re-scheduling is
initiated by unexpected changes. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A TWO-PHASE CONSTRUCTIVE HEURISTIC FOR PERMUTATION
FLOW-SHOP SCHEDULING PROBLEM MINIMIZING TOTAL COMPLETION TIME </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Kaveh
Sheibani <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Iran
Telecommunication Research Centre (ITRC) Tehran, Iran <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext;mso-bidi-font-weight:normal">Abstract.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal;mso-bidi-font-weight:bold"> This paper describes a
polynomial-time heuristic for the permutation flow-shop scheduling problem with
the criterion of minimizing total completion time. The proposed method consists
of two phases: arranging the jobs in priority order and then constructing a
sequence. A new ranking method is employed to prioritize the jobs for
incorporating into the construction phase of the heuristic. Computational
experiments using standard benchmark problems indicate the proposed method is
very effective.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal"><o:p></o:p></span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">OPTIMAL CONTROL OF A MEAN-REVERTING INVENTORY </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abel
Cadenillas, Peter Lakner and Michael Pinedo<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Alberta Edmonton, Canada <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">New
York University New York, USA <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext;mso-bidi-font-weight:normal">Abstract.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal;mso-bidi-font-weight:bold"> In this paper we consider the
inventory level of a company and assume that it follows a mean reverting
process. The objective of the management is to keep this inventory level as
close as possible to a given target; there is a running cost associated with
the difference between the inventory level and the target. The management is
allowed to perform at times interventions in the form of major purchases or
sales of the goods. These interventions are subject to fixed as well as
proportional costs. The objective of this paper is to find the levels of the
inventory at which management should perform interventions and the magnitudes
of these interventions that minimize the expected total discounted cost.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext;font-weight:normal"><o:p></o:p></span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">DESIGN OF SINGLE-FEATURED EWMA-X CONTROL CHART FOR PROCESS
MEAN SHIFT DETECTION </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Chi-Shuan
Liu and Fang-Chih Tien <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">National
Taipei University of Technology Taipei, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The control chart is a useful process monitoring technique for statistical
process control (SPC). Identifying both large and small process mean shifts is
an important issue in this area. Currently, a combined EWMA-X chart is commonly
used in practice, but two sets of statistics and control limits are required to
be calculated and plotted. The objective of this paper is to simplify the
original combined chart in order to perform the process monitoring with one set
of statistic and control limits. Therefore, a new control chart, so called
SFEWMA-X chart, is designed and proposed. An experiment was performed to show
the proposed chart can identify both small and large process mean shift with
the same detection power. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">ECONOMIC DESIGN OF <span style="mso-bidi-font-style:italic">X</span>
CONTROL CHARTS UNDER PREVENTIVE MAINTENANCE AND TAGUCHI LOSS FUNCTIONS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Fong-Jung
Yu, Yu-Hua Lin and Ruey-Shiang Guh<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Da-Yeh
University, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Hsiuping
Institute of Technology, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">National
Formosa University, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Economic designs of x control charts have been widely investigated and insure
that the economic design of control chart actually has a lower cost. A
preventive maintenance can reduce the failure rate to an out-of-control state
by an amount proportional to the preventive maintenance level. This paper
presents an integrated model for combining the preventive maintenance and the
economic design of x control charts using Taguchi loss function. The
maintenance activities are coordinated with the statistical characteristics of
the sampling results. A numerical example is also used to demonstrate the
model’s working underlying the effect of preventive maintenance on the quality
control costs. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">OPTIMIZING AN INVENTORY CONTROL SYSTEM IN MAZANDARAN WOOD
AND PAPER INDUSTRIES IN IRAN </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">T
Mojibi, R Tavakkoli-Moghaddam and VA Rezaei-Nosrati<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Islamic
Azad University - Firoozkuh Branch, Firoozkuh, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">College
of Engineering, University of Tehran, Tehran, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Mazandaran
Wood and Paper Industries, Sari, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">This paper considers an inventory control system in a
real case study, namely Mazandaran Wood and Paper Industries in Iran. By
optimizing the existing situation of such a system, we can find the ordering
and holding costs resulting in a reduction of the total inventory cost. We
calculate the economic order quantity (EOQ) and re-order point (ROP). Six items
of raw materials are taken into account, which are considered about 94% of the
warehouse's inventories as a sample in our study. The related result show that
the total cost is reduced by 41% in the optimized inventory control system. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">EXPLORING BENEFITS, OPPORTUNITIES, COSTS AND RISKS OF
TERRITORIAL TRANSFORMATIONS: A COMBINED ANALYTIC NETWORK PROCESS (ANP) MODEL
AND DRIVING FORCES-PRESSURES - STATE - IMPACTS - RESPONSES (DPSIR) FRAMEWORK
FOR ENVIRONMENTAL ASSESSMENT </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Marta
Bottero and Valentina Ferretti <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Politecnico
di Torino Torino Italy <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">Environmental Assessment of territorial transformation
projects is an intrinsically complex multidimensional process, because it
considers different elements, such as the physical-chemical, biological,
cultural and socio-economic components. The use of decision support methods
therefore can be beneficial for decision makers. When talking referring to
Environmental Assessment and territorial transformations, a very consolidated
approach that is used to report information concerning the various aspects of
the development is the one that makes use of indicators. Of these methods, it
is worth mentioning a recent approach presented by the Organization for Economic
Co-operation and Development where environmental indicators have been organized
according to the so-called Driving forces- Pressures- State-Impacts- Responses
(DPSIR) framework. Unfortunately, this approach results in a linearity in the
relationships between the actions of a project, the impacts on the
environmental system and the interferences with human activities and thus fails
to study the system complexity in depth. In order to overcome the limits of
this approach, this paper proposes a combined decision support tool that
employs the DPSIR environmental indicator framework to analyse the different
environmental aspects of the problem and the Analytic Network Process (ANP)
method to manage the interdependencies among the factors, which can be organized
in categories of Benefits, Opportunities, Costs and Risks (BOCR structure). The
paper illustrates the application of the combined DPSIR/ANP model according to
the BOCR structure to assess three alternative projects for the re
qualification of a downgraded urban area in Northern Italy. The results show
the most relevant environmental indicators which describe the transformation
and the ranking of the three considered options. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A COMBINATION OF QUALITY FUNCTION DEPLOYMENT (QFD) AND
ANALYTIC NETWORK PROCESS (ANP) TO EVALUATE URBAN REDEVELOPMENT PROJECTS. AN
APPLICATION TO THE “BELLE DE MAI – LA FRICHE” OF MARSEILLE (FRANCE) </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Isabella
M Lami and Elena L Vitti <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Polytechnic
of Turin Turin, Italy <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This paper proposes a methodological framework to integrate stakeholders’
requirements and different aspects of urban redevelopment projects. We propose
the application of the multi criteria decision analysis techniques combined of
Quality Function Deployment (QFD) and Analytic Network Process (ANP) in order
to evaluate the revitalization projects for areas where an industrial past has
vanished from an economical point of view, but still remains in the character
of the buildings and the area. This work illustrates the application of the
methodological framework in order to evaluate the principals aspects of the
transformation of the site “Belle de Mai – La friche” in Marseille, a former
tobacco factory where, since the early 1990s, the 45,000 square meter have been
a centre for contemporary cultural and artistic events. Trough a combination of
QFD and ANP we intend to verify the possibility of this procedure can
contribute to the decision-making process and the general consensus. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">OPTIMIZATION OF SALES PROMOTION ACTIVITIES FOR CUSTOMERS
UNDER THE CONDITION OF BUDGET CONSTRAINT </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Susumu
Saito and Hisashi Kikuchi <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Tokyo
University of Science Japan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"> The
purpose of this study is to create a model of sales promotion activities to
each customer where the summation of expected profits under budget constraint
is maximized, as a multi-dimensional knapsack problem, where the purchase
probability of a customer for various channels is already known. In addition,
we have proposed a metaheuristic algorithm for that problem. This problem has
been formulated using a defined expected cost, an expected profit, and a risk
measure that is the square root of a semi-variance of risks. We could obtain
the tool to decide “to whom and how (channel) what sort of products should be
promoted” in order to maximize an expected total profit under a budget
constraint and a risk tolerance. The relation among an expected total profit, a
budget and a risk tolerance were also obtained. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">FUZZY SUBSET HOOD MEASURE APPLIED IN WEIGHTS SETTING OF
DECISION MAKERS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Cheng-Chuang
Hon, Yan-Kuen Wu and Ling-Lang Tang<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Ming
Hsin University of Science and Technology, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Vanung
University, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Yuan-Ze
University, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">In order to avoid deviations caused by autocratic and
subjective attitudes in decision making process, bringing decision makers (DMs)
together to obtain group consensus is one of the best choices for achieving
accurate performance. Decision weighting of each decision maker (DM) is set
equally in traditional performance evaluation model. Actually it is more
suitable to be set by means of mutual interactions within decision group. This
paper summarized some methodologies, Similarity Aggregation Method (SAM),
Optimal Aggregation Method (OAM), Least Squares Distance Method (LSDM),
Defuzzification-based Least Squares Method (DLSM), to define the weights
setting of DMs. Also a new developed method called Subset hood Aggregation
Method (SbAM) is provided for the same purpose, which can be used for getting
more objective group consensus. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">AN APPROXIMATE REASONING APPROACH TO RANK THE RESULTS OF
FUZZY QUERIES </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Christer
Carlsson, Robert Fuller and Jozsef Mezei <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abo
Akademi University Turku, Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
In this paper we suggest the use of a context-dependent fuzzy aggregation
method to rank the results of fuzzy queries over fuzzy ontologies. In our
approach the fuzzy aggregation rules are provided by the experts, the
coefficients of the consequence part of the rules are derived from the
linguistic values used in the conditional part of the rules and the rank of a
search result is determined by the Takagi-Sugeno fuzzy reasoning scheme. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">USING MULTIPLE CRITERIA DECISION-MAKING METHOD TO ANALYZE
OPTIMUM PUSH/PULL JUNCTION POINT LOCATION FOR TFT-LCD MANUFACTURING </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Taho
Yang, Jiunn-chenn Lu and Ling-Hsiu Chen<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Institute
of Manufacturing Information and Systems National Cheng Kung University Tainan,
Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Chaoyang
University of Technology Taichung County, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This research’s aim is to implement a hybrid push/pull production system that
can satisfy both high service-levels and low inventory cost. Simultaneously, we
consider sophisticated variability, such as multi-products, random setup,
indiscriminate break-downs, yield loss, batch processes, and other
contingencies. The problem can be solved by a multiple criteria decision-making
method (MCDM). A technique for order-preference by similarity-to-ideal solution
(TOPSIS) is used to select a suitable option. The optimization involves
evaluation of stochastic performance measures within alternative scenarios
among potential junction point locations using a discrete event simulation
model. A practical thin film transistor-liquid crystal display (TFT-LCD)
process case-study is utilized to illustrate the proposed method. Simulation results
indicate that the inventory cost was reduced by over 46% after implementing a
hybrid push/pull production strategy. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">ADOPTING MULTI-CLASS MTS TO PREDICT THE OBSTRUCTIVE SLEEP
APNEA </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Li-Fei
Chen, Pa-Chun Wang, Chun-Chin Hsu and Chao-Ton Su<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Fu-Jen
Catholic University, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Cathay
General Hospital, School of Medicine, Fu Jen Catholic University, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Chaoyang
University of Technology, Taiwan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">National
Tsing Hua University, Taiwan <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext;mso-bidi-font-weight:normal">Abstract.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal;mso-bidi-font-weight:bold"> This study aims to apply the
Multi-Mahalanobis Taguchi System (MMTS), based on anthropometric information
and questionnaire data, to predict obstructive sleep apnea (OSA). We separated
the collected OSA data into two parts: group I and group II. The group I data
were used to establish the MMTS model, and group II’s data were used to test
the developed MMTS model. The results show that MMTS has an accuracy of 0.8438
on the OSA prediction. Therefore, MMTS can be applied to assist doctors in
foreseeing the diagnosis of OSA before running the PSG test, so the medical
resources can be used more effectively.</span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext;font-weight:normal"><o:p></o:p></span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A FUZZY MODEL OF MEDICAL DISASTER RESPONSE: DECISION MAKING
SUPPORT AND DISASTER MANAGEMENT TOOL FOR CZECH EMERGENCY MEDICAL RESCUE
SERVICES </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Jan
Stoklasa <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Palacky
University Olomouc Olomouc, Czech Republic <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">The decision making process of the Emergency medical
rescue services operations centre during disasters involves a significant
amount of uncertainty. Decisions need to be made quickly and no mistakes are
tolerable, particularly in the case of disasters resulting in large number of
injured people. A multiphase linguistic fuzzy model is introduced to assist the
operator during the initial phase of the medical disaster response. Based on
uncertain input data, we can estimate the severity of the disaster, the number
of injured people, and the amount of forces and resources needed to
successfully deal with the situation. The need of reinforcements is also
considered. Fuzzy numbers, linguistic variables and fuzzy rule bases are
applied to deal with the uncertainty. Results derived by the model are
available both as fuzzy sets and linguistic terms. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">REAL ASSET APPRAISAL BASED ON A MULTI-EXPERT APPROACH USING
THE PAY-OFF METHOD FOR REAL OPTION VALUATION </span><span style="font-size:
9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Mikael
Collan and Mario Fedrizzi<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Institute
for Advanced Management Systems Research Åbo Akademi University Turku, Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Trento Trento, Italy <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The pay-off method is a novel method that is designed for the valuation and
analysis of real assets. The method is based on cash-flow scenarios that are
used to create a pay-off distribution for a project, from which the real option
value is calculated. The reliability of the used cash-flow scenarios influences
the reliability of the analysis results. Evaluation of future cash-flows is a
complicated issue, as it is often impossible to identify or specify in
sufficient detail any relevant processes that underlie the real asset
cash-flows. This means that often the best information available on the future
of the cash-flows that the asset generates is in the heads of project managers
/ experts. Managers’ opinions about the future may not be in concert thus
calling for consensus building. In this paper we show how consensus on project
dynamics can be modelled and how the resulting cash-flows can be used as a
basis for real an analysis of project profitability with the payoff method. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">CASH FLOW SIMULATION EMBEDDED REAL OPTIONS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Tero
Haahtela <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Aalto
BIT Research Centre School of Science and Technology, Aalto University Aalto,
Finland <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Cash flow simulation embedded option is an option whose value is based on
choosing the optimal decision in each time step during a single cash flow
calculation simulation run. Cash flow simulation embedded options are mostly
operative options with continuous, gradual and nearly immediate exercise with
well-known payoff or benefits. Typically these options are difficult to model
with other methods than Monte Carlo simulation. However, cash flow simulation
embedded options and the common, once exercisable options can be applied simultaneously
in an investment valuation by using the simulated cash flow with embedded
options as the underlying asset for the lattice, which is then used in valuing
other lattice type options and their interactions. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">DEFAULT ABLE BONDS UNDER IMPRECISE INFORMATION </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Elettra
Agliardi and Rossella Agliardi <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Bologna Italy <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This article develops a computational method to implement the effect of
imperfect information on the value of default able bonds. A fuzzy modelling is
adopted and the numerical experiments show that an imprecise value of the
stochastic underlying asset and/or the barrier triggering the default have
material impact on the qualitative shape of the term structures of credit
spreads. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">APPLYING FINANCIAL RIGOUR TO FUZZY REAL OPTIONS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Sebastian
Jaimungal and Yuri Lawryshyn <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Toronto Toronto, ON, Canada <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Fuzzy numbers have recently been introduced in the real options literature as a
simple alternative to option valuation. However, so far the assumption that the
project value is a fuzzy number has not been put on solid theoretical ground.
Here, we consider two methods to value a Real Options project whose future
expected cash owes are based on managerial triangular estimates. Both methods
rely on correlating a geometric Brownian motion (GBM) process to a traded
market security or index. By utilizing the minimal entropy martingale measure,
we value the real option in a theoretically sound manner. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">REAL TIME REDUNDANCY STUDY OF A TIME DEPENDENT FAILURE
RATES MODEL </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Mani
Sharifi, Soroush Bafekr Mishamandani and Sara Harati Zadeh<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Islamic
Azad University, Qazvin branch, Qazvin, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Islamic
Azad University, Kashan branch, Kashan, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Islamic
Azad University, Karaj Branch Karaj, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
In this paper we study a useful model in redundancy systems. This model has (<span style="mso-bidi-font-style:italic">n </span>+ 1 ) components that <span style="mso-bidi-font-style:italic">n</span> components are spare parts of the
main component. The failure rate of the working component is time dependent as
λ<span style="mso-bidi-font-style:italic">.t</span>δ and the failure rates of
non working components are zero. When a component stops working, one of the
spare parts start working immediately. The failed components are non
repairable. In this model we establish the differential equations between the
system states and by solve these equations; we calculate some parameters of the
system like the reliability and MTTF in real time situation. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">APPLICATIONS OF AGENT-BASED MODELS FOR OPTIMIZATION
PROBLEMS: A LITERATURE REVIEW </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">M
Barbati, G Bruno and A Genovese<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Naples Naples, Italy <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of Sheffield Sheffield, UK <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.
</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">This work is devoted to the illustration of the
application of Agent-Based Modelling (ABM) to optimization problems. Indeed,
given their peculiarity in dealing with the representation and the simulation
of complex systems, ABMs have been recently applied (sometimes combined to
other optimization techniques) to solve optimization problems whose domains
present several interrelated components in a distributed and heterogeneous
environment. Thus, a first comparison among agent-based approaches and
classical optimization techniques will be provided, followed by an extensive
review aimed at evaluating the impact of these methodologies in the Operational
Research / Management Science (OR/MS) literature. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">EFFICIENT LOWER BOUNDING SCHEMES FOR THE MULTI-COMMODITY
CAPACITATED MULTI-FACILITY WEBER PROBLEM </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">M
Hakan Akyüz, Temel Öncan and İ Kuban Altinel<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Galatasaray
University Istanbul, Turkey <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Boğaziçi
University Istanbul, Turkey <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The Multi-commodity Capacitated Multi-facility Weber Problem (MCMWP) is
concerned with locating <span style="mso-bidi-font-style:italic">I</span>
capacitated facilities in the plane satisfying the demands of <span style="mso-bidi-font-style:italic">J </span>customers for <span style="mso-bidi-font-style:italic">K</span> types of commodities subject to
bundle constraints on commodity flows between facilities and customers. We
propose a Lagrangean relaxation (LR) scheme where the sub problem is solved by
column generation procedure on an equivalent Set Covering problem. To enhance
the Sub gradient Optimization algorithm, two efficient acceleration strategies
are applied. We also propose a block norm based lower bounding approach which
employs approximate Mixed Integer Linear Programming formulations of the MCMWP.
The proposed lower bounding schemes are tested on randomly generated test
instances. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">SYSTEM PERFORMANCE UNDER COST RESTRICTIONS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Frank
Beichelt <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">University
of the Witwatersrand Johannesburg, Republic of South Africa <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This contribution deals with maximizing the availability of a technical system
under a repair cost limit replacement policy: After a system failure occurring
at system age <span style="mso-bidi-font-style:italic">t</span> the necessary
cost for repairing the system is estimated. If this cost exceeds a certain
limit <span style="mso-bidi-font-style:italic">c</span>(<span style="mso-bidi-font-style:
italic">t</span>), called repair cost limit, the system is replaced by an equivalent
new one. Otherwise, the failure is removed by repairing the system. The
corresponding system availability is determined and minimized with respect to
special classes of decreasing repair cost limit functions <span style="mso-bidi-font-style:italic">c</span>(<span style="mso-bidi-font-style:
italic">t</span>). The results give strong evidence in favour of the hypothesis
that applying a decreasing repair cost limit is more efficient than applying a
constant repair cost limit. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">AUCTIONING HETEROGENEOUS ITEMS WITH APPLICATIONS TO
INTERNET ADVERTISEMENTS AND PRIVATIZATIONS </span><span style="font-size:9.0pt;
font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Yumiko
Baba <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Aoyamagakuin
University Tokyo, Japan <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
We analyze auctions with multiple similar, but heterogeneous items. Bidders’
preferences among the items are common, but bidders value the same item
differently. Therefore, the model has both common value component and private
value component. We show that the sequential sealed-bid first-price auction
achieves both efficiency and revenue maximization simultaneously. This
mechanism is used by a Japanese advertisement company to sell internet keyword
to sponsors and is very different from the mechanism used by the US search
engines such as Google and Yahoo. The mechanism is also applicable to privatization
problem. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">DIVERSIFICATION EFFECTS OF ASSET PRICE PROCESS PARAMETERS:
AN EMPIRICAL INVESTIGATION </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Ursula
Walther and Andrey Fetsun<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Frankfurt
School of Finance and Management, Germany <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">BHF
Bank AG, Germany <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Higher moments of asset price distributions – especially skewness – have long
been recognized as important characteristics in asset pricing and portfolio
management. The three moment capital asset pricing model (3M CAPM) considers
skewness in addition to mean and variance, the final asset pricing equation
containing the linear factor gamma that describes standardized co-skewness. In
an asset management context the assumption of a general preference for positive
skewness leads to different efficient sets and portfolio choice. A less well
known fact is the diversification behavior of skewness when several assets are
blended in a portfolio. It repeatedly has been found that skewness is not
“diversified away” even in large portfolios. In some studies the market
portfolio even shows a higher negative skewness than most of the individual
asset. Therefore, the expectation of a general diversification benefit for
asset characteristics other than variance is misleading. Unwanted portfolio
characteristics may even accumulate on the portfolio level. In our study we
investigate the diversification effects of a broad set of asset characteristics
in a systematic way. The starting point is the description of asset price
behavior as parameterized stochastic processes using a rich set of parameters.
We follow the two-step approach frequently used in financial risk management:
firstly we estimate the time varying volatility by a GARCH-type model; then, we
capture the remaining characteristics by fitting a parameterized probability
distribution to the standardized returns. For the latter we use the family of
NIG distributions. This provides a set of seven to eight parameters that
detailed but systematically describe the asset characteristics. This estimation
approach is applied to a broad data set of daily returns of German large and
small cap stocks. In order to study diversification effects we systematically
select assets showing distinctive parameter levels and analyze the historical
price processes of buy-and-hold-portfolios. We also study the behavior of
portfolios created by the aggregation of simulated single asset portfolio
returns. The results confirm the observation of non-diversification effects
with respect to skewness. Additionally we find interesting and systematic
effects on other parameters that give new insights into the behavior of stock
returns on an aggregated level. <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">TYPOLOGIES OF FOREST FIRES IN THE MEDITERRANEAN AREA
ACCORDING TO HUMAN ACTIVITY </span><span style="font-size:9.0pt;font-family:
&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;mso-fareast-font-family:
&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;
color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">M
Martínez-Gómez, M Marí-Benlloch, C Maroto and J Suárez <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Universidad
Politécnica de Valencia Valencia, Spain <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
Important economic losses and deaths are caused every year by forest fires;
these also deteriorate natural resources and increase pollution. We need
rigorous analysis of the factors that cause them to reduce their effects, and
to develop tools in order to minimize their consequences. First, we selected
the main variables to classify the human activity factors and the
characteristics of the forest fires. Once the variables were defined, we
classified the municipalities (using a land zoning of a Mediterranean area -
Autonomous Region of Valencia) with homogeneous characteristics of incidence
and causes of forest fires using multivariate techniques and Geographical
Information Systems (GIS). <o:p></o:p></span></p>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

</div>

<div>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">OPEN STATION MIXED-MODEL ASSEMBLY LINES: A CASE OF A NEWLY
ESTABLISHED LINE </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Babak
H. Tabrizi and Reza Tavakkoli-Moghaddam <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">College
of Engineering, University of Tehran Tehran, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This paper considers a special case of mixed-model assembly lines (MMALs). As
each station assembly time is one of the fundamental parameters in setting the
number of stations and operators and also providing an accurate production
schedule, we need to investigate circumstances in which operators are
inexperienced and perform their task within a time interval rather than in an
exact time considering corresponding learning function. The strategy of
Value-at-Risk (VaR) is applied to tackle with mentioned uncertainty as an
efficient pmedian approach in manipulating potential risk. The objective is to
minimize the utility and idle time costs in open station cases, incurred when
the line is not balanced because of lack of homogeneity in each station
throughput time. A numerical example is tested at the end to demonstrate the
different results obtained from an ordinary problem compared with its analogous
stochastic one. <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">A POSSIBILISTIC PROGRAMMING SOLUTION METHOD FOR A
BI-OBJECTIVE OPEN SHOP SCHEDULING PROBLEM WITH FUZZY PARAMETERS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Reza
Tavakkoli-Moghaddam, Samaneh Noori Darvish and Nikbakhsh Javadian<o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">College
of Engineering, University of Tehran Tehran, Iran <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Mazandaran
University of Science and Technology Babol, Iran <o:p></o:p></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext;mso-bidi-font-weight:normal">Abstract.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal;mso-bidi-font-weight:bold"> This paper presents a novel,
bi-objective possibilistic mixed- integer linear programming model for an open
shop scheduling problem. Machine-dependent setup times, fuzzy processing times
and fuzzy due dates with triangular possibility distributions are the main
constrains of this model. The objectives are to minimize the total weighted
tardiness and total weighted completion times. An interactive fuzzy programming
solution approach proposed by Torabi and Hassini (TH) is applied to convert the
original model into an auxiliary single objective crisp model. By the use of a
classic approach given in the literature, some numerical instances in small
sizes are generated at random and solved in order to obtain the Pareto optimal
solutions.</span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal"><o:p></o:p></span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">IS TIMING MONEY? THE RETURN SHAPING EFFECT OF TECHNICAL
TRADING SYSTEMS </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Peter
Scholtz <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Frankfurt
School of Finance and Management Frankfurt, Germany <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
The success of trading systems based on technical analysis still seems puzzling
and is controversial discussed among experts. In practice, technical trading is
widely accepted, whereas academics are traditionally rather skeptical. But in
the late 1980s, the picture started to change: the prominent study written by
Brock et al. (1992) analyzed the profitability of technical trading rules and
found strong support for the predictability of stock returns from past returns.
They concluded that the damnation of technical analysis might have been
premature. Since then, the subject of technical analysis became somehow
acceptable in the academic circle and more and more empirical studies were
conducted, which provided an extensive analysis (for a literature review, see Park
&amp; Irwin 2007). However, the previous research is predominantly based on
historical back tests and bootstraps of different markets. This work
investigates the hypothesis that trend following systems should profit from
auto correlated returns and contributes to recent literature by trying to
answer the questions why, i.e. under which circumstances trading systems may
work.<span style="mso-bidi-font-weight:bold"><o:p></o:p></span></span></p>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-hansi-theme-font:major-latin;mso-bidi-font-family:
Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

</span></h2>

<h2 align="left" style="margin:0cm;margin-bottom:.0001pt;text-align:left;
line-height:normal"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;
mso-ascii-theme-font:major-latin;mso-fareast-font-family:&quot;Times New Roman&quot;;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext;
font-weight:normal">SCHEDULING PROBLEMS FOR LOGISTIC PLATFORMS WITH FIXED
STAIRCASE COMPONENT ARRIVALS AND VARIOUS DELIVERIES HYPOTHESES </span><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-fareast-font-family:&quot;Times New Roman&quot;;mso-hansi-theme-font:major-latin;
mso-bidi-font-family:Arial;color:windowtext"><o:p></o:p></span></h2>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Susana
Carrera, Wahiba Ramdane-Cherif and Marie-Claude Portmann <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">INPL-LORIA,
ENSMN, Parc de Saurupt Nancy, France <o:p></o:p></span></p>

<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">Abstract.</span></b><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">
This paper studies the scheduling problem within a logistic platform node. It
corresponds to the last node in the supply chain located just before the final
customers. In this node, customer orders are prepared using known quantities of
components received from the suppliers. For upstream flows, trucks deliver
known component quantities at fixed times. For downstream flows, optimized
customer delivery tours are planned at fixed times except the last one which
will be done at a flexible time corresponding to the end of the schedule. We
consider a simplified case of one bottleneck-assembling machine. Several sub
cases are considered depending on the number of the fixed and flexible
deliveries and also on the chosen criteria. For each sub case, upper and lower
bounds are proposed and compared experimentally on heterogeneous instance
families. All the ingredients are therefore available to design a branch and
bound for these new scheduling problems.<o:p></o:p></span></p>

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mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">

<hr size="2" width="100%" noshade style="color:#A0A0A0" align="left">

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<p align="left" style="margin-bottom:0cm;margin-bottom:.0001pt;text-align:left"><span style="font-size:9.0pt;font-family:&quot;Cambria&quot;,&quot;serif&quot;;mso-ascii-theme-font:major-latin;
mso-hansi-theme-font:major-latin;mso-bidi-font-family:Arial;color:windowtext">©
ORLab Analytics Inc.<o:p></o:p></span></p>

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