Copula estimation of distribution algorithms based on exchangeable Archimedean copula

Authors:
Lifang Wang;Xiaodong Guo;Jianchao Zeng;Yi Hong
Affiliations:
College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China/ Complex System and Computational Intelligence Laboratory, Taiyuan University of Science ...;Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, 030024, China.;Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, 030024, China.;College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
Venue:
International Journal of Computer Applications in Technology
Year:
2012

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Abstract

The two key operators in estimation of distribution algorithms (EDAs) are estimating the distribution model according to the selected population and sampling new individuals from the estimated model. Copula EDA introduces the copula theory into EDA. The copula theory provides the theoretical basis and the way to separate the multivariate joint distribution probability function into a function called copula and the univariate margins. The estimation operator and the sampling operator in copula EDA are discussed in this paper, and three exchangeable Archimedean copulas are used in copula EDA. The experimental results show that the three copula EDAs perform equivalently to some classical EDAs.