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Detailed schedule
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Thursday 30 January:
Thursday 11:15-12:30 TA-1: COMEX - Optimization 1 Room Vesale 023 - Chair: M. Schyns
Thursday 11:15-12:30 TA-2: Software and Implementation Room Vesale 020 - Chair: M. Mezmaz
Thursday 11:15-12:30 TA-3: COMEX - Smart mobility Room Vesale 025 - Chair: A. Caris
Thursday 11:15-12:30 TA-4: Systems Room Pentagone 0A11 - Chair: P. Kunsch
Thursday 14:00-15:40 TB-1: Data Analysis 1 Room Vesale 023 - Chair: X.Siebert
Thursday 14:00-15:40 TB-2: Multiple Objectives Room Vesale 020 - Chair: Y. de Smet
Thursday 14:00-15:40 TB-3: Logistics Room Vesale 025 - Chair: D. De Wolf
Thursday 14:00-15:40 TB-4: COMEX - Applications to Economy Room Pentagone 0A11 - Chair: W. Brauers
Thursday 14:00-15:40 TB-5: Networks Room Pentagone 0A07 - Chair: B. Fortz
Thursday 16:10-17:25 TC-1: Mixed-integer nonlinear programming Room Vesale 023 - Chair: Y. Crama
Thursday 16:10-17:25 TC-2: Decision Analysis 1 Room Vesale 020 - Chair: S. Eppe
Thursday 16:10-17:25 TC-3: Routing Room Vesale 025 - Chair: K. Sörensen
Thursday 16:10-17:25 TC-4: Graphs Room Pentagone 0A11 - Chair: H. Mélot
Thursday 16:10-17:25 TC-5: Scheduling Room Pentagone 0A07 - Chair: S. Hanafi
Friday 9:00-10:15 FA-1: Queuing Room Vesale 023 - Chair: S. Wittevrongel
Friday 9:00-10:15 FA-2: Decision Analysis 2 Room Vesale 020 - Chair: R. Bisdorff
Friday 9:00-10:15 FA-3: COMEX - Optimization 2 Room Vesale 025 - Chair: M. Labbé
Friday 9:00-10:15 FA-4: Production Room Pentagone 0A11 - Chair: D. Tuyttens
Friday 14:00-15:40 FB-1: Data Analysis 2 Room Vesale 023 - Chair: P. Fortemps
- The carry-over effect does exist in tennis
Dries Goossens (Ghent University) Co-authors: Frits Spieksma
- Alternative Pairwise Decomposition Techniques for Label Ranking
Massimo Gurrieri (UMONS) Co-authors: Philippe Fortemps, Xavier Siebert
- Constrained Clustering using Column Generation
Behrouz Babaki (KU Leuven) Co-authors: Tias Guns, Siegfried Nijssen Abstract: In recent years, it is realised that many problems in data mining can be seen as pure optimisation problems. In this work, we investigate the problem of constraint-based clustering from an optimisation
point of view. The use of constraints in clustering is a recent development and allows to encode prior believes about desirable clusters. This paper proposes a new solution for constrained minimum-sum-of-squares clustering. Contrary to most earlier approaches, it is exact and provides a fundamental approach for including constraints. The proposed approach uses column generation in an integer linear programming setting. The key insight is that clustering constraints can be pushed into a branch-and-bound algorithm for solving subproblems of a column generation process. Experimental results show the feasibility of the approach, while at the same time raising a number of challenges related to the master problem. We believe this problem can act as a challenging benchmark for branch-and-price techniques.
- Geometrical lower bound for the nonnegative rank of slack matrices
Julien Dewez (Université catholique de Louvain) Co-authors: Nicolas Gillis, François Glineur
Friday 14:00-15:40 FB-2: Heuristics Room Vesale 020 - Chair: T. Stützle
Friday 14:00-15:40 FB-3: COMEX - Transportation Room Vesale 025 - Chair: F. Spieksma
Friday 14:00-15:40 FB-4: Health Room Pentagone 0A11 - Chair: G. Vanden Berghe
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