ORBEL 24

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Detailed schedule

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Thursday 28, 2010
8:30-9:00Registration - Welcome coffee
9:00-9:30Welcoming session - Room 030
9:30-10:30Plenary session: P. Baptiste
Sustainable Development: How can we help

Room 030
10:30-11:00Coffee break
11:00-12:40Parallel sessions
  Timetabling in education and sport
Chair: G. Vanden Berghe
Room: 126
Transportation management
Chair: F. Semet
Room: 130
Networks
Chair: B. Fortz
Room: 138
Nonconvex optimization 1
Chair: F. Bach
Room: 035
12:40-14:00Lunch (and board meeting)
14:00-15:40Parallel sessions
  Constraint programming models 1
Chair: Y. Deville
Room: 126
Vehicle routing
Chair: S. Limbourg
Room: 130
Combinatorial optimization and IP applications
Chair: Q. Louveaux
Room: 138
Nonconvex Optimization 2
Chair: R. Sepulchre
Room: 035
15:40-16:10Coffee break
16:10-17:50Parallel sessions
  Constraint programming models 2
Chair: P. Schaus
Room: 126
Performance modeling
Chair: G. Janssens
Room: 130
Scheduling
Chair: K. Sorensen
Room: 138
Planning under uncertainty
Chair: R. Leus
Room: 035
17:50-General Assembly (Room 138)
18:45-Conference dinner

Friday 29, 2010
9:00-10:40Parallel sessions
  Metaheuristics
Chair: J. Teghem
Room: 126
Production and distribution (9:25)
Chair: Y. Arda
Room: 130
Multiple criteria
Chair: R. Bisdorff
Room: 138
Stochastic models (9:25)
Chair: L. Esch
Room: 035
10:40-11:00Coffee break
11:00-12:40Parallel sessions
  Constraint programming and Supply Chain Management
Chair: Y. Deville
Room: 126
OR in health management
Chair: P. De Causmaecker
Room: 130
Rankings and importance indices
Chair: JL. Marichal
Room: 138
Queueing
Chair: S. Wittevrongel
Room: 035
12:40-14:00Lunch
14:00-15:00Plenary session: M. Goemans
The Power of Matroids

Room 030
15:10-16:00Parallel sessions
  Optimization software
Chair: E. Loute
Room: 126
Integrated operations planning
Chair: B. Raa
Room: 130
Cycles in graphs
Chair: F. Spieksma
Room: 138
 
16:00-16:35Plenary session: ORBEL award and closing session
Room 030
16:35-...Coffee break
Show all the abstracts
Thursday 11:00:00 Timetabling in education and sport
Room 126 - Chair: G. Vanden Berghe

Thursday 11:00:00 Transportation management
Room 130 - Chair: F. Semet

Thursday 11:00:00 Networks
Room 138 - Chair: B. Fortz

Thursday 11:00:00 Nonconvex optimization 1
Room 035 - Chair: F. Bach

Thursday 14:00:00 Constraint programming models 1
Room 126 - Chair: Y. Deville

Thursday 14:00:00 Vehicle routing
Room 130 - Chair: S. Limbourg

Thursday 14:00:00 Combinatorial optimization and IP applications
Room 138 - Chair: Q. Louveaux

Thursday 14:00:00 Nonconvex Optimization 2
Room 035 - Chair: R. Sepulchre

Thursday 16:10:00 Constraint programming models 2
Room 126 - Chair: P. Schaus

Thursday 16:10:00 Performance modeling
Room 130 - Chair: G. Janssens

Thursday 16:10:00 Scheduling
Room 138 - Chair: K. Sorensen

Thursday 16:10:00 Planning under uncertainty
Room 035 - Chair: R. Leus

Friday 09:00:00 Metaheuristics
Room 126 - Chair: J. Teghem

Friday 09:25:00 Production and distribution (9:25)
Room 130 - Chair: Y. Arda

Friday 09:00:00 Multiple criteria
Room 138 - Chair: R. Bisdorff

Friday 09:25:00 Stochastic models (9:25)
Room 035 - Chair: L. Esch
  • Extra-Small Scenario Trees for Multistage Stochastic Programming
    Boris Defourny (University of Liege)
    Co-authors: Damien Ernst and Louis Wehenkel
  • Extinction Probability of a Branching Process in a Markovian Random Environment
    Sophie Hautphenne (Université Libre de Bruxelles)
    Co-authors: Guy Latouche
  • A clustering approach to estimate route travel time distributions
    Wouter Charle (K.U.Leuven)
    Co-authors: Francesco Viti, Chris M.J. Tampère
    Abstract:
    Accurate network travel time estimation is today one of the most challenging problems in trac theory. The mainstream research on travel time estimation concentrates on the estimation of mean route travel time or some measures of travel time reliability (i.e. 10th and 90th percentiles). However, given the growing detail in travel time measurements it is also possible to estimate route travel time distributions. This serves a broader spectrum of applications and provides more useful information. For this goal, this research presents a method to calculate the travel time histogram of a route, based on link travel time observations. The aim of this new method is to allow the development of an advanced route planner that is able to optimize route choice reliability. The notion of reliability is de ned by the end-user of the route planner and highly depends on the properties of the route travel time distribution. Central in the development of the route planner is the distinction between (cheap) o -line storage and computations and (expensive) on-line computations. For that it is important to minimize the on-line computational e ort of calculating a route travel time histogram. The method described in this study can be deployed beyond route planning applications and the eld of trac management. Other applications can be for instance the location optimization of logistic hubs (i.e. airports, packaging services, . . . ) or public services (i.e. hospitals, re stations, . . . ) and the evaluation of network performance.

Friday 11:00:00 Constraint programming and Supply Chain Management
Room 126 - Chair: Y. Deville

Friday 11:00:00 OR in health management
Room 130 - Chair: P. De Causmaecker

Friday 11:00:00 Rankings and importance indices
Room 138 - Chair: JL. Marichal

Friday 11:00:00 Queueing
Room 035 - Chair: S. Wittevrongel

Friday 15:10:00 Optimization software
Room 126 - Chair: E. Loute

Friday 15:10:00 Integrated operations planning
Room 130 - Chair: B. Raa

Friday 15:10:00 Cycles in graphs
Room 138 - Chair: F. Spieksma

 
 
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