ORBEL 27

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Detailed schedule

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Thursday 7 February:

9:00-9:30Registration (Room Spina)
9:30-10:45Plenary session
Welcome
Invited speaker: El-Ghazali Talbi
Metaheuristics for multi-objective optimization - A unified view
10:45-11:15Coffee break
11:15-12:30Parallel sessions
  TA-1: COMEX Decision Making
Chair: B. Fortz
Room: C.611
TA-2: Production 1
Chair: E.h. AGhezzaf
Room: C.601
TA-3: Global Optimization
Chair: D. Claeys
Room: C.602
TA-4: Transportation 1
Chair: C. Vanovermeire
Room: C.603
12:30-14:00Lunch
14:00-15:40Parallel sessions
  TB-1: COMEX Health
Chair: G. Vanden Berghe
Room: C.611
TB-2: Routing
Chair: G.K. Janssens
Room: C.601
TB-3: Meta-Heuristics
Chair: P. Vansteenwegen
Room: C.602
TB-4: Transportation 2
Chair: F.C.R Spieksma
Room: C.603
15:40-16:10Coffee break
16:10-17:25Parallel sessions
  TC-1: COMEX Routing
Chair: K. Sôrensen
Room: C.611
TC-2: Sets, Relations and Rankings
Chair: B. De Baets
Room: C.601
TC-3: Logistics
Chair: S. Demeyer
Room: C.602
 
17:30-General Assembly (Room C.611)
19:30-Conference dinner (Carlton)

Friday 8 February
9:00-10:15Parallel sessions
  FA-1: COMEX Logistics
Chair: Y. Crama
Room: C.611
FA2: Production 2
Chair: D. Tuyttens
Room: C.611
FA-3: MIP
Chair: T. Dokka
Room: C.603
 
10:15-10:40Coffee break
10:40-12:40Plenary session
ORBEL Award
Wolsey award announcement
Invited speaker: Andrea Schaerf
Educational Timetabling: Problems, Benchmarks, Algorithms, Software Tools, and Practical Issues
12:40-14:00Lunch
14:00-14:30IMinds Information Session (Room C.611)
14:30-16:10Parallel sessions
  FB-1: COMEX automatic tuning and organization
Chair: T. Stützle
Room: C.611
FB2: Disaster, Water and Biology
Chair: L. Porretta
Room: C.602
FB-3: Decision Making
Chair: D. Goossens
Room: C.603
 
16:10-16:40Coffee break


Thursday 11:15-12:30 TA-1: COMEX Decision Making
Room C.611 - Chair: B. Fortz

Thursday 11:15-12:30 TA-2: Production 1
Room C.601 - Chair: E.h. AGhezzaf

Thursday 11:15-12:30 TA-3: Global Optimization
Room C.602 - Chair: D. Claeys

Thursday 11:15-12:30 TA-4: Transportation 1
Room C.603 - Chair: C. Vanovermeire

Thursday 14:00-15:40 TB-1: COMEX Health
Room C.611 - Chair: G. Vanden Berghe

Thursday 14:00-15:40 TB-2: Routing
Room C.601 - Chair: G.K. Janssens

Thursday 14:00-15:40 TB-3: Meta-Heuristics
Room C.602 - Chair: P. Vansteenwegen

Thursday 14:00-15:40 TB-4: Transportation 2
Room C.603 - Chair: F.C.R Spieksma

Thursday 16:10-17:25 TC-1: COMEX Routing
Room C.611 - Chair: K. Sôrensen

Thursday 16:10-17:25 TC-2: Sets, Relations and Rankings
Room C.601 - Chair: B. De Baets

Thursday 16:10-17:25 TC-3: Logistics
Room C.602 - Chair: S. Demeyer

Friday 9:00-10:15 FA-1: COMEX Logistics
Room C.611 - Chair: Y. Crama

Friday 9:00-10:15 FA2: Production 2
Room C.611 - Chair: D. Tuyttens

Friday 9:00-10:15 FA-3: MIP
Room C.603 - Chair: T. Dokka

Friday 14:00-15:40 FB-1: COMEX automatic tuning and organization
Room C.611 - Chair: T. Stützle

Friday 14:00-15:40 FB2: Disaster, Water and Biology
Room C.602 - Chair: L. Porretta

Friday 14:00-15:40 FB-3: Decision Making
Room C.603 - Chair: D. Goossens
  • Progressive multi-objective optimization (PDF)
    Kenneth Sörensen (Universiteit Antwerpen)
    Co-authors: Johan Springael
    Abstract:
    The multi-objective optimization paradigm prescribes that a decision maker should first generate a set of non-dominated solutions and then pick a solution from this set according to his/her preferences, using a multi-criteria method of his/her choice. In some situations, however, this approach is of limited practical use, mainly because of the fact that multi-criteria methods were not designed with the output of a typical multi-objective optimization algorithm in mind. Multi-objective optimization methods typically generate a large set of non-dominated solutions --- in fact the quality of a multi-objective method depends partially on the cardinality of the Pareto set it generates --- whereas multi-criteria methods were designed to compare only a handful of alternatives. In ijitdm01 we introduced progressive multi-objective optimization (PMOO) that attempts to overcome the drawbacks of the multi-objective paradigm. PMOO is a novel technique that includes the decision maker's preferences into the multi-objective optimization process instead of tackling these steps sequentially. pmoo integrates a method for multi-criteria decision making into a simple multi-objective metaheuristic by maintaining and updating a small reference archive of non-dominated solutions throughout the search. In this talk, we present a PMOO method for the multi-objective knapsack problem. This approach integrates the well-known PROMETHEE multi-criteria method into a simple tabu search method. By applying this novel technique to a set of instances of the multi-objective knapsack problem, the superiority of PMOO over the commonly accepted sequential approach of generating a Pareto set approximation first and selecting a single solution afterwards is demonstrated.
  • Elicitation procedures for the comparison of decisional maps (PDF)
    Valérie Brison (UMONS, Faculté Polytechnique)
    Co-authors: Marc Pirlot
  • Designing a combinatorial auction for Solids (PDF)
    Dries Goossens (KU Leuven)
    Co-authors: Frits Spieksma, Sander Onderstal, Jan Pijnacker
  • On a queue with customer deadlines (PDF)
    Tom Maertens (Ghent University)
    Co-authors: Herwig Bruneel

 
 
  SOGESCI/ORBEL - Conference chair: Prof. P. De Causmaecker - Platform: Prof. M. Schyns