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Proceedings Paper

Two new mutation operators for enhanced search and optimization in evolutionary programming
Author(s): Kumar Chellapilla; David B. Fogel
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Paper Abstract

Evolutionary programming (EP) has been successfully applied to many parameter optimization problems. We propose a mean mutation operator, consisting of a linear combination of Gaussian and Cauchy mutations. Preliminary results indicate that both the adaptive and non-adaptive versions of the mean mutation operator are capable of producing solutions that are as good as, or better than those produced by Gaussian mutations alone. The success of the adaptive operator could be attributed to its ability to self-adapt the shape of the probability density function that generates the mutations during the run.

Paper Details

Date Published: 13 October 1997
PDF: 10 pages
Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); doi: 10.1117/12.279596
Show Author Affiliations
Kumar Chellapilla, Villanova Univ. (United States)
David B. Fogel, Natural Selection, Inc. (United States)

Published in SPIE Proceedings Vol. 3165:
Applications of Soft Computing
Bruno Bosacchi; James C. Bezdek; David B. Fogel, Editor(s)

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