Comparing two constraint handling techniques in a binary-coded genetic algorithm for optimization problems

Authors:
Helio J. C. Barbosa;Afonso C. C. Lemonge;Leonardo G. Fonseca;Heder S. Bernardino
Affiliations:
Laboratório Nacional de Computação Científica, Petrópolis, RJ, Brazil;Universidade Federal de Juiz de Fora, Juiz de Fora, MG, Brazil;Universidade Federal do Espírito Santo, São Mateus, ES, Brazil;Laboratório Nacional de Computação Científica, Petrópolis, RJ, Brazil
Venue:
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Year:
2010

Citing 3
Cited 0

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Stochastic ranking for constrained evolutionary optimization

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Abstract

In this paper the relative performance of two constraint handling techniques, namely a parameter-less adaptive penalty method (APM) and the stochastic ranking method (SR), is studied in the context of continuous parameter constrained optimization problems. Both techniques are used within the same search engine, a binary-coded genetic algorithm.