Recombination and Self-Adaptation in Multi-objective Genetic Algorithms

Bruno Sareni (1) , Jérémi Regnier (1) , Xavier Roboam (1)

1 LEEI - Laboratoire électrotechnique et électronique industrielle

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.

Mots clés: Genetic algorithms; Multiobjective optimization; Self-adaptation; Recombination operators

Domaines: Algorithme et structure de données [cs.DS]; Optimisation et contrôle [math.OC]; Energie électrique

Bruno Sareni, Jérémi Regnier, Xavier Roboam. Recombination and Self-Adaptation in Multi-objective Genetic Algorithms. Lecture Notes in Computer Science, 2004, vol. 2936, pp.115-126. ⟨10.1007/978-3-540-24621-3_10⟩. ⟨hal-00766887⟩