Constraint and Integer Programming

Constraint and Integer Programming.- 1 Introduction.- 2 CP(FD) Basic Concepts.- 3 Integer Linear Programming Basic Concepts.- 4 Incomplete search strategies.- 5 Conclusion.- References.- Two Generic Schemes for Efficient and Robust Cooperative Algorithms.- 1 Introduction.- 2 Operations Research Algorithms and Constraint Programming.- 3 Operations Research Algorithms and Mixed Integer Programming.- 4 Constraint Programming and Mixed Integer Programming.- 5 Operations Research Algorithms and Local Search.- 6 Mixed Integer Programming and Local Search.- 7 Constraint Programming and Local Search.- References.- Branch-and-Infer: A Framework for Combining CP and IP.- 1 Introduction.- 2 Modeling in CP and IP.- 3 An illustrating example: discrete tomography.- 4 Branch and Infer.- 5 Symbolic constraints in IP.- 6 Example: Symbolic constraints for supply chain planning.- 7 Summary.- References.- Global Constraints and FiItering Algorithms.- 1 Introduction.- 2 Global Constraints.- 3 Filtering Algorithms.- 4 Two Successful Filtering Algorithms.- 5 Global Constraints and Over-eonstrained Problems.- 6 Quality of Filtering Algorithms.- 7 Discussion.- 8 Conclusion.- References.- Exploiting relaxations in CP.- 1 Introduction and Motivation.- 2 Integer Linear Programming and Relaxations.- 3 Integrating Relaxations in CP.- 4 Relax to propagate.- 5 Relax to guide the search.- 6 A case study: global optimization constraints for a Path constraint.- References.- Hybrid Problem Solving in ECLiPSe.- 1 Introduction.- 2 Integration of Constraints and Operations Research.- 3 Language Ingredients for Hybrid Solvers.- 4 ECLiPSe as a Platform for Building Hybrid Aigorithms.- 5 Programming a Hybrid Search in ECLiPSe.- 6 Conclusion.- References.- CP Based Branch-and-Price.- 1 Introduction.- 2 Three Illustrative Examples.- 3 Implementation Issues.- 4 Future Directions for CP Based Branch-and-Price.- References.- Randomized Backtrack Search.- 1 Introduction.- 2 Randomization of Backtrack Search Methods.- 3 Formal Models of Heavy-Tailed Behavior.- 4 Heavy and Fat-Tailed Distributions.- 5 Heavy and Fat-Tailed Distributions in Backtrack Search.- 6 Restart Strategies.- 7 Portfolio Strategies.- 8 Conclusions.- References.- Local Search and Constraint Programming.- LS and CP ilLustrated on a transportation Problem.- 1 Introduction.- 2 A didactic transportation problem.- 3 A CP approach for dTP.- 4 Constructive Algorithms.- 5 LS as Post-Optimization.- 6 Metaheuristics.- 7 LS during construction.- 8 Conclusions.- References.- Open Perspectives.- 1 Motivations, Challenges and Applications.- 2 Transforming Models to Aigorithms.- 3 New Techniques.- 4 New Application Areas.- References.