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Recombination and Self-Adaptation in Multi-objective Genetic Algorithms

Sareni, Bruno and Régnier, Jérémi and Roboam, Xavier Recombination and Self-Adaptation in Multi-objective Genetic Algorithms. (2004) Lecture Notes in Computer Sciences, 2936. 115-126. ISSN 0302-9743

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Official URL: http://dx.doi.org/10.1007/978-3-540-24621-3_10


This paper investigates the influence of recombination and self-adaptation in real-encoded Multi-Objective Genetic Algorithms (MOGAs). NSGA-II and SPEA2 are used as example to characterize the efficiency of MOGAs in relation to various recombination operators. The blend crossover, the simulated binary crossover and the breeder genetic crossover are compared for both MOGAs on multi-objective problems of the literature. Finally, a self-adaptive recombination scheme is proposed to improve the robustness of MOGAs.

Item Type:Article
Additional Information:Thanks to Springer verlag. The original publication is available at http://link.springer.com/. Special issue : 6th International Conference, Evolution Artificielle, EA 2003, Marseilles, France, October 27-30, 2003, Revised Selected Papers
HAL Id:hal-00766887
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Laboratory name:
Deposited On:19 Dec 2012 10:01

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