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On the Design of Diploid Genetic Algorithms for Problem Optimization in Dynamic Environments

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conference contribution
posted on 14.11.2008, 10:02 by Shengxiang Yang
Using diploidy and dominance is one method to enhance the performance of genetic algorithms in dynamic environments. For diploidy genetic algorithms, there are two key design factors: the cardinality of genotypic alleles and the uncertainty in the dominance scheme. This paper investigates the effect of these two factors on the performance of diploidy genetic algorithms in dynamic environments. A generalized diploidy and dominance scheme is proposed for diploidy genetic algorithms, where the cardinality of genotypic alleles and/or the uncertainty in the dominance scheme can be easily tuned and studied. The experimental results show the efficiency of increasing genotypic cardinality rather than introducing uncertainty in the dominance scheme.

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Citation

2006 IEEE Congress on Evolutionary Computation, Proceedings of, pp. 1362-1369

Published in

2006 IEEE Congress on Evolutionary Computation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

isbn

0780394879

Copyright date

2006

Available date

14/11/2008

Publisher version

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1688467

Language

en

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