A New Hybrid Evolution Genetic Algorithm with Laplace Crossover and Power Mutation

Author

Ma, Xinshun

Author_Institution

Dept. of Math. & Phys., North China Electr. Power Univ., Baoding, China

Volume

2

fYear

2009

fDate

11-14 Dec. 2009

Firstpage

88

Lastpage

91

Abstract

In this study, we develop a new genetic algorithm based on hybrid Laplace crossover and power mutation (HLCPM). This hybrid evolution algorithm makes use of feasible as well as infeasible real-coded chromosomes to initialize population. In genetic evolution, the hybrid crossover operation, which rests on Laplace distribution, is taken place between feasible and infeasible chromosomes, and the mutation operation is based on power distribution function. The performance of HLCPM is discussed with number computation on a set of 10 benchmark global optimization test problems, and the results show that HLCPM has a quite well performance.

Keywords

Laplace equations; genetic algorithms; Laplace distribution; hybrid Laplace crossover and power mutation; hybrid evolution genetic algorithm; power distribution function; real-coded chromosomes; Biological cells; Computational intelligence; Constraint optimization; Distribution functions; Genetic algorithms; Genetic mutations; Mathematics; Physics; Security; Testing; Laplace distribution; genetic algorithm; hybrid crossover; power distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2009. CIS '09. International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-5411-2

Type

conf

DOI

10.1109/CIS.2009.64

Filename

5375946