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Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

5th International Conference, CPAIOR 2008 Paris, France, May 20-23, 2008 Proceedings

  • Conference proceedings
  • © 2008

Overview

Editors:
  1. Laurent Perron
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  2. Michael A. Trick
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5015)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: CPAIOR 2008.

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About this book

The 5th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2008) was held in Paris, France May 20–23, 2008. The purpose of this conference series is to bring together researchers in the ?elds of constraint programming, arti?cial intelligence, and operations research to explore ways of solving large-scale, practical optimization problems through integration and hybridization of the ?elds’ di?erent techniques. Through the years, this research community is discovering that the ?elds have much in c- mon, and there has been tremendous richness in the resulting cross-fertilization of ?elds. This year, we allowed submissions of both long (15 page) and short (5 page) papers, with short papers either being original work, a reduced version of a long paper, or an extended abstract of work published elsewhere. We were not s- prised by the 69 submissions in the long paper category: this is an active ?eld with many researchers. We were surprised by the 61 short paper submissions. This was far more than predicted. With 130 high-quality submissions, compe- tion for acceptance in this year’s program was particularly ?erce. In the end, we accepted 18 long papers and 22 short papers for presentation and publication in this volume.

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Table of contents (43 papers)

  1. Front Matter

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  3. Long Papers

    1. Constraint Integer Programming: A New Approach to Integrate CP and MIP

      • Tobias Achterberg, Timo Berthold, Thorsten Koch, Kati Wolter
      Pages 6-20

    2. New Filtering for the \(\mathit{cumulative}\) Constraint in the Context of Non-Overlapping Rectangles

      • Nicolas Beldiceanu, Mats Carlsson, Emmanuel Poder
      Pages 21-35

    3. Multi-stage Benders Decomposition for Optimizing Multicore Architectures

      • Luca Benini, Michele Lombardi, Marco Mantovani, Michela Milano, Martino Ruggiero
      Pages 36-50

    4. Fast and Scalable Domino Portrait Generation

      • Hadrien Cambazard, John Horan, Eoin O’Mahony, Barry O’Sullivan
      Pages 51-65

    5. Gap Reduction Techniques for Online Stochastic Project Scheduling

      • Grégoire Dooms, Pascal Van Hentenryck
      Pages 66-81

    6. Integrating Symmetry, Dominance, and Bound-and-Bound in a Multiple Knapsack Solver

      • Alex S. Fukunaga
      Pages 82-96

    7. Cost Propagation – Numerical Propagation for Optimization Problems

      • Birgit Grohe, Dag Wedelin
      Pages 97-111

    8. Fitness-Distance Correlation and Solution-Guided Multi-point Constructive Search for CSPs

      • Ivan Heckman, J. Christopher Beck
      Pages 112-126

    9. Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting

      • Lukas Kroc, Ashish Sabharwal, Bart Selman
      Pages 127-141

    10. The Accuracy of Search Heuristics: An Empirical Study on Knapsack Problems

      • Daniel H. Leventhal, Meinolf Sellmann
      Pages 142-157

    11. A Novel Approach For Detecting Symmetries in CSP Models

      • Christopher Mears, Maria Garcia de la Banda, Mark Wallace, Bart Demoen
      Pages 158-172

    12. Amsaa: A Multistep Anticipatory Algorithm for Online Stochastic Combinatorial Optimization

      • Luc Mercier, Pascal Van Hentenryck
      Pages 173-187

    13. Optimal Deployment of Eventually-Serializable Data Services

      • Laurent Michel, Alexander Shvartsman, Eldine Sonderegger, Pascal Van Hentenryck
      Pages 188-202

    14. Counting Solutions of Knapsack Constraints

      • Gilles Pesant, Claude-Guy Quimper
      Pages 203-217

    15. From High-Level Model to Branch-and-Price Solution in G12

      • Jakob Puchinger, Peter J. Stuckey, Mark Wallace, Sebastian Brand
      Pages 218-232

    16. Simpler and Incremental Consistency Checking and Arc Consistency Filtering Algorithms for the Weighted Spanning Tree Constraint

      • Jean-Charles Régin
      Pages 233-247
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