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Communication dans un congrès

Optimization by hybridization of a genetic algorithm with CSP techniques

Nicolas Barnier 1 
1 MAIA-OPTIM - ENAC Equipe MAIAA-OPTIM
MAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien
Abstract : Within the framework of Constraint Logic Programming on finite domains (CLP(FD)), we introduce a new optimization method based on a Genetic Algorithm (GA) and designed for combinatorial problems whose search spaces are too large and/or objective functions too complex for usual Constraint Satisfaction Problem (CSP) techniques and whose constraints are too complex for conventional genetic algorithm. The main idea is the handling of sub-domains of the CSP variables by the genetic algorithm. The population of the genetic algorithm is made up of strings of sub-domains whose fitness are computed through the resolution of the corresponding "sub-CSPs" which are somehow much easier than the original problem. We provide basic and dedicated recombination and mutation operators with various degrees of robustness. The first set of experimentations adresses a naive formulation of the Vehicle Routing Problem (VRP) and the Radio Link Frequency Assignement Problem (RLFAP). The results are quite encouraging as we outperform CLP(FD) techniques and genetic algorithm alone.
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Communication dans un congrès
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Soumis le : jeudi 17 avril 2014 - 16:33:32
Dernière modification le : mardi 19 octobre 2021 - 11:02:56
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  • HAL Id : hal-00937706, version 1

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Nicolas Barnier. Optimization by hybridization of a genetic algorithm with CSP techniques. ESSLLI 97, 9th European Summer School in Logic, Language and Information, Aug 1997, Aix-en-Provence, France. pp xxxx. ⟨hal-00937706⟩

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