2010•Computer Engineering and Applications JournalRequires access

Dual population differential evolution algorithm based on crossover and mutation strategy

Xuedong Wu

Open publisher page 2 citations

Abstract

Dual Population Differential Evolution algorithm based on Crossover and Mutation strategy(CMDPDE) is proposed to enhance global search ability of single population differential evolution.In CMDPDE,one population uses big scale factor and crossover factor,the other with small scale factor and crossover factor will execute crossover or mutation operations to search better individual after an evolution for each individual evolves one time per generation.At the same time evolution information will be exchanged between two populations after all individuals of two populations evolve ten times.Compared with single population differential evolution,CMDPDE increases diversity of solutions through dual population and crossover and mutation strategy,which makes CMDPDE search better solutions in a larger range.Experiment results on six benchmark functions show that CMDPDE has the better ability of finding optimal solution.

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What this paper is about

Dual Population Differential Evolution algorithm based on Crossover and Mutation strategy(CMDPDE) is proposed to enhance global search ability of single population differential evolution.In CMDPDE,one population uses big scale factor and crossover factor,the other with small scale factor and crossover factor will execute crossover or mutation operations to search better individual after an evolution for each individual evolves one time per generation.At the same time evolution information will be exchanged between two populations after all individuals of two populations evolve ten times.Compared with single population differential evolution,CMDPDE increases diversity of solutions through dual population and crossover and mutation strategy,which makes CMDPDE search better solutions in a larger range.Experiment results on six benchmark functions show that CMDPDE has the better ability of finding optimal solution.

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Available abstract

Dual Population Differential Evolution algorithm based on Crossover and Mutation strategy(CMDPDE) is proposed to enhance global search ability of single population differential evolution.In CMDPDE,one population uses big scale factor and crossover factor,the other with small scale factor and crossover factor will execute crossover or mutation operations to search better individual after an evolution for each individual evolves one time per generation.At the same time evolution information will be exchanged between two populations after all individuals of two populations evolve ten times.Compared with single population differential evolution,CMDPDE increases diversity of solutions through dual population and crossover and mutation strategy,which makes CMDPDE search better solutions in a larger range.Experiment results on six benchmark functions show that CMDPDE has the better ability of finding optimal solution.

Key concepts: Crossover, Differential evolution, Mutation, Population, Benchmark (surveying), Dual (grammatical number), Scale factor (cosmology), Mathematical optimization

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