Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5846
Title: On the design of diploid genetic algorithms for problem optimization in dynamic environments
Authors: Yang, S
Keywords: Genetic algorithms
Issue Date: 2006
Publisher: IEEE
Citation: IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, BC: 1362 - 1369, Sep 2006
Abstract: 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.
Description: Tihis article is posted here with permission from the IEEE - Copyright @ 2006 IEEE
URI: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1688467
http://bura.brunel.ac.uk/handle/2438/5846
DOI: http://dx.doi.org/10.1109/CEC.2006.1688467
ISBN: 0-7803-9487-9
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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