13 October 1997 Two new mutation operators for enhanced search and optimization in evolutionary programming
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kumar Chellapilla, Kumar Chellapilla, David B. Fogel, David B. Fogel, } "Two new mutation operators for enhanced search and optimization in evolutionary programming", Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); doi: 10.1117/12.279596; https://doi.org/10.1117/12.279596
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