Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5885
Title: Dominance learning in diploid genetic algorithms for dynamic optimization problems
Authors: Yang, S
Keywords: Diploid genetic algorithms;Dominance change scheme;Dominance learning;Dynamic optimization problems
Issue Date: 2006
Publisher: ACM
Citation: 8th Annual Conference on Genetic and Evolutionary Computation (GECCO'06)_, Seattle, Washington, USA: 1435 - 1436, 8 - 12 Jul 2007
Abstract: This paper proposes an adaptive dominance mechanism for diploidy genetic algorithms in dynamic environments. In this scheme, the genotype to phenotype mapping in each gene locus is controlled by a dominance probability, which is learned adaptively during the searching progress and hence is adapted to the dynamic environment. Using a series of dynamic test problems, the proposed dominance scheme is compared to two other dominance schemes for diploidy genetic algorithms. The experimental results validate the efficiency of the proposed dominance learning scheme.
Description: Copyright @ 2006 Yang
URI: http://bura.brunel.ac.uk/handle/2438/5885
DOI: http://dx.doi.org/10.1145/1143997.1144232
ISBN: 1-59593-186-4
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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