Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/6607
Title: Learning the dominance in diploid genetic algorithms for changing optimization problems
Authors: Yang, S
Keywords: Diploid representation;Dominance scheme;Genetic algorithms (GAs);Genotype;Phenotype
Issue Date: 2007
Citation: 2nd International Symposium on Intelligence Computation and Applications, Wuhan, China, 21-23 September 2007, pp 157-162
Abstract: Using diploid representation with dominance scheme is one of the approaches developed for genetic algorithms to address dynamic optimization problems. This paper proposes an adaptive dominance mechanism for diploid 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 learnt adaptively during the searching progress. The proposed dominance scheme isexperimentally compared to two other schemes for diploid genetic algorithms. Experimental results validate the efficiency of the dominance learning scheme.
URI: http://bura.brunel.ac.uk/handle/2438/6607
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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