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

R?gin Jean-Charles Rueher Michel

ISBN 10: 354021836X / ISBN 13: 9783540218364

Edité par Springer, 2004

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pp. 436.

N° de réf. du vendeur 183109012

Détails bibliographiques

• Titre: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
• Éditeur: Springer
• Date de parution: 2004
• Langue: anglais
• ISBN à 10 chiffres: 354021836X
• ISBN à 13 chiffres: 9783540218364
• Reliure: Couverture souple
• État de l'article: Used

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Synopsis

This volume contains the proceedings of the First International Conference on IntegrationofAIandORTechniquesinConstraintProgrammingforCombina- rialOptimisation Problems.This new conferencefollows the seriesof CP-AI-OR International Workshops on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimisation Problems held in Ferrara (1999), Paderborn (2000), Ashford (2001), Le Croisic (2002), and Montreal (2003). The success of the previous workshops has demonstrated that CP-AI-OR is bec- ing a major forum for exchanging ideas and methodologiesfrom both ?elds. The aim of this new conference is to bring together researchersfrom AI and OR, and to give them the opportunity to show how the integration of techniques from AI and OR can lead to interesting results on large scale and complex problems. The integration of techniques from Arti?cial Intelligence and Operations - search has provided e?ective algorithms for tackling complex and large scale combinatorial problems with signi?cant improvements in terms of e?ciency, scalability and optimality. The bene't of this integration has been shown in applications such as hoist scheduling, rostering, dynamic scheduling and vehicle routing. At the programming and modelling levels, most constraint languages embed OR techniques to reason about collections of constraints, so-calledglobal constraints. Some languages also provide support for hybridization allowing the programmer to build new integrated algorithms. The resulting multi-paradigm programmingframeworkcombines the exibility and modelling facilities of C- straint Programming with the special purpose and e?cient methods from - erations Research.