A Species Conserving Genetic Algorithm for Multimodal Function Optimization

This paper introduces a new technique called species conservation for evolving paral-lel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the speci...

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Bibliographic Details
Published inEvolutionary computation Vol. 10; no. 3; pp. 207 - 234
Main Authors Li, Jian-Ping, Balazs, Marton E., Parks, Geoffrey T., Clarkson, P. John
Format Journal Article
LanguageEnglish
Published One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01.09.2002
Subjects
Algorithms
Genetic algorithms
Genetics, Population
Models, Genetic
multimodal functions
niching
Population Density
species
species conservation
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Summary:This paper introduces a new technique called species conservation for evolving paral-lel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current gen-eration are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimiza-tion problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.
Bibliography:Fall, 2002
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ISSN:1063-6560
1530-9304
DOI:10.1162/106365602760234081