Integration of AI and OR Techniques in Constraint Programming

1. Front Matter

   Pages I-XXV

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2. A Time-Dependent No-Overlap Constraint: Application to Urban Delivery Problems

   • Penélope Aguiar Melgarejo, Philippe Laborie, Christine Solnon

   Pages 1-17

3. Rectangle Placement for VLSI Testing

   • Merav Aharoni, Odellia Boni, Ari Freund, Lidor Goren, Wesam Ibraheem, Tamir Segev

   Pages 18-30

4. A Constraint-Based Local Search for Edge Disjoint Rooted Distance-Constrained Minimum Spanning Tree Problem

   • Alejandro Arbelaez, Deepak Mehta, Barry O’Sullivan, Luis Quesada

   Pages 31-46

5. A Benders Approach to the Minimum Chordal Completion Problem

   • David Bergman, Arvind U. Raghunathan

   Pages 47-64

6. MaxSAT-Based Scheduling of B2B Meetings

   • Miquel Bofill, Marc Garcia, Josep Suy, Mateu Villaret

   Pages 65-73

7. Embedding Decision Trees and Random Forests in Constraint Programming

   • Alessio Bonfietti, Michele Lombardi, Michela Milano

   Pages 74-90

8. Scheduling with Fixed Maintenance, Shared Resources and Nonlinear Feedrate Constraints: A Mine Planning Case Study

   • Christina N. Burt, Nir Lipovetzky, Adrian R. Pearce, Peter J. Stuckey

   Pages 91-107

9. Learning Value Heuristics for Constraint Programming

   • Geoffrey Chu, Peter J. Stuckey

   Pages 108-123

10. Derivative-Free Optimization: Lifting Single-Objective to Multi-Objective Algorithm

    • Cyrille Dejemeppe, Pierre Schaus, Yves Deville

    Pages 124-140

11. Branching on Multi-aggregated Variables

    • Gerald Gamrath, Anna Melchiori, Timo Berthold, Ambros M. Gleixner, Domenico Salvagnin

    Pages 141-156

12. Time-Table Disjunctive Reasoning for the Cumulative Constraint

    • Steven Gay, Renaud Hartert, Pierre Schaus

    Pages 157-172

13. Uncertain Data Dependency Constraints in Matrix Models

    • C. Gervet, S. Galichet

    Pages 173-181

14. An Efficient Local Search for Partial Latin Square Extension Problem

    • Kazuya Haraguchi

    Pages 182-198

15. Enhancing MIP Branching Decisions by Using the Sample Variance of Pseudo Costs

    • Gregor Hendel

    Pages 199-214

16. BDD-Guided Clause Generation

    • Brian Kell, Ashish Sabharwal, Willem-Jan van Hoeve

    Pages 215-230

17. Combining Constraint Propagation and Discrete Ellipsoid-Based Search to Solve the Exact Quadratic Knapsack Problem

    • Wen-Yang Ku, J. Christopher Beck

    Pages 231-239

18. Large Neighborhood Search for Energy Aware Meeting Scheduling in Smart Buildings

    • Boon Ping Lim, Menkes van den Briel, Sylvie Thiébaux, Russell Bent, Scott Backhaus

    Pages 240-254

19. ILP and CP Formulations for the Lazy Bureaucrat Problem

    • Fabio Furini, Ivana Ljubić, Markus Sinnl

    Pages 255-270

20. The Smart Table Constraint

    • Jean-Baptiste Mairy, Yves Deville, Christophe Lecoutre

    Pages 271-287

This book constitutes the proceedings of the 12th International Conference on the Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, CPAIOR 2015, held in Barcelona, Spain, in May 2015. The 29 papers presented together with 8 short papers in this volume were carefully reviewed and selected from 90 submissions. The purpose of the conference series is to bring together researchers in the fields of Constraint Programming, Artificial Intelligence and Operations Research to explore ways of solving hard and large scale combinatorial optimization problems that emerge in various industrial domains. Pooling the skills and strengths of this diverse group of researchers has proved extremely effective and valuable during the past decade leading to improvements and cross-fertilization between the three fields as well as breakthrough for actual applications.

• algorithms
• artificial intelligence
• combinatorial optimization
• comparison of models
• constraint and logic programming
• continuous scheduling
• declarative programming
• dynamic programming
• graph algorithms
• heuristic functions construction
• local search
• metaheuristics
• mixed integer programming
• modeling methodologies
• operations research
• optimization
• search methodologies
• sequence mining
• static analysis
• uncertainty

• University of Connecticut, Storrs, USA

  Laurent Michel

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