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1 Laboratoire d-Informatique, Signaux, et Systèmes de Sophia-Antipolis I3S - Groupe SCOBI MDSC - Modèles Discrets pour les Systèmes Complexes 2 DOLPHIN - Parallel Cooperative Multi-criteria Optimization LIFL - Laboratoire d-Informatique Fondamentale de Lille, Inria Lille - Nord Europe

Abstract : Choosing the suitable representation, the operators and the values of the parameters of an evolutionary algorithm is one of the main problems to design an efficient algorithm for one particular optimization problem. This additional information to the evolutionary algorithm generally is called the algorithm parameter, or parameter. This work introduces a new evolutionary algorithm, States based Evolutionary Algorithm which is able to combine different evolutionary algorithms with different parameters included different representations in order to control the parameters and to take the advantage of each possible evolution algorithm during the optimization process. This paper gives first experimental arguments of the efficiency of the States based EA.

Keywords : evolutionary algorithms parameters settings parameters control parallel evolutionary algorithms





Autor: Sébastien Verel - Philippe Collard - Manuel Clergue -

Fuente: https://hal.archives-ouvertes.fr/



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