Applying family competition to evolution strategies for constrained optimization

Jinn-Moon Yang, Ying-ping Chen, Jorng Tzong Horng, Cheng Yan Kao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

71 Scopus citations

Abstract

This paper applies family competition to evolution strategies to solve constrained optimization problems. The family competition of Family Competition Evolution Strategy (FCES) can be viewed as a local competition involving the children generated from the same parent, while the selection is a global competition among all of the members in the population. According to our experimental results, the self-adaptation of strategy parameters with deterministic elitist selection may trap ESs into local optima when they are applied to heavy constrained optimization problems. By controlling strategy parameters with non-self adaptive rule, FCES can reduce the computation time of self-adaptive Gaussian mutation, diminish the complexity of selection from (m+l) to (m+m), and avoid to be premature. Therefore, FCES is capable of obtaining better performance and saving the computation time. In this paper, FCES is compared with other evolutionary algorithms on various benchmark problems and the results indicate that FCES is a powerful optimization technique.

Original languageEnglish
Title of host publicationEvolutionary Programming VI - 6th International Conference, EP 1997, Proceedings
EditorsPeter J. Angeline, John R. McDonnell, Robert G. Reynolds, Russ Eberhart
PublisherSpringer Verlag
Pages201-211
Number of pages11
ISBN (Print)9783540627883
DOIs
StatePublished - 1 Jan 1997
Event6th International Conference on Evolutionary Programming, EP 1997 - Indianapolis, United States
Duration: 13 Apr 199716 Apr 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1213
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Evolutionary Programming, EP 1997
CountryUnited States
CityIndianapolis
Period13/04/9716/04/97

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