A species conserving genetic algorithm for multimodal function optimization.

No === 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 th...

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Main Authors:	Li, Jian-Ping, Balazs, M.E., Parks, G.T., Clarkson, P.J.
Language:	en
Published:	2009
Subjects:	Genetic algorithms Multimodal functions Niching Species Species conservation
Online Access:	http://hdl.handle.net/10454/3532

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spelling	ndltd-BRADFORD-oai-bradscholars.brad.ac.uk-10454-35322019-08-31T03:02:25Z A species conserving genetic algorithm for multimodal function optimization. Li, Jian-Ping Balazs, M.E. Parks, G.T. Clarkson, P.J. Genetic algorithms Multimodal functions Niching Species Species conservation No 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. 2009-09-29T08:01:53Z 2009-09-29T08:01:53Z 2002 Article No full-text available in the repository Li, J.P., Balazs, M.E., Parks, G.T. and Clarkson, P.J. (2002). A species conserving genetic algorithm for multimodal function optimization. Evolutionary Computation. Vol. 10, No. 3, pp. 207-234. http://hdl.handle.net/10454/3532 en http://dx.doi.org/10.1162/106365602760234081
collection	NDLTD
language	en
sources	NDLTD
topic	Genetic algorithms Multimodal functions Niching Species Species conservation
spellingShingle	Genetic algorithms Multimodal functions Niching Species Species conservation Li, Jian-Ping Balazs, M.E. Parks, G.T. Clarkson, P.J. A species conserving genetic algorithm for multimodal function optimization.
description	No === 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.
author	Li, Jian-Ping Balazs, M.E. Parks, G.T. Clarkson, P.J.
author_facet	Li, Jian-Ping Balazs, M.E. Parks, G.T. Clarkson, P.J.
author_sort	Li, Jian-Ping
title	A species conserving genetic algorithm for multimodal function optimization.
title_short	A species conserving genetic algorithm for multimodal function optimization.
title_full	A species conserving genetic algorithm for multimodal function optimization.
title_fullStr	A species conserving genetic algorithm for multimodal function optimization.
title_full_unstemmed	A species conserving genetic algorithm for multimodal function optimization.
title_sort	species conserving genetic algorithm for multimodal function optimization.
publishDate	2009
url	http://hdl.handle.net/10454/3532
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A species conserving genetic algorithm for multimodal function optimization.

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