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
  • On the best low multilinear rank approximation of higher-order tensors
    Mariya Ishteva (Université catholique de Louvain, Department of Mathematical Engineering)
    Co-authors: PA. Absil, S. Van Huffel, L. De Lathauwer
  • Regression on fixed-rank positive semidefinite matrices: a geometric approach
    Gilles Meyer (University of Liège)
    Co-authors: Gilles Meyer, Silvère Bonnabel and Rodolphe Sepulchre
  • Generalized Power Method for Sparse Principal Component Analysis
    Rodolphe Sepulchre (Université de Liège)
    Co-authors: Michel Journée, Peter Richtarik, Yurii Nesterov
    Abstract:
    In this paper we develop a new approach to sparse principal component analysis (sparse PCA). We propose two single-unit and two block optimization formulations of the sparse PCA problem, aimed at extracting a single sparse dominant principal component of a data matrix, or more components at once, respectively. While the initial formulations involve nonconvex functions, and are therefore computationally intractable, we rewrite them into the form of an optimization program involving maximization of a convex function on a compact set. The dimension of the search space is decreased enormously if the data matrix has many more columns (variables) than rows. We then propose and analyze a simple gradient method suited for the task. It appears that our algorithm has best convergence properties in the case when either the objective function or the feasible set are strongly convex, which is the case with our single-unit formulations and can be enforced in the block case. Finally, we demonstrate numerically on a set of random and gene expression test problems that our approach outperforms existing algorithms both in quality of the obtained solution and in computational speed.
  • A pooling approach for the feed mixing problem
    Jannes Verstichel (KaHo Sint-Lieven)
    Co-authors: G. Vanden Berghe, H. Callens

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

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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