Pair-copula estimation of distribution algorithms

  • Authors:
  • Huimin Gao;Xiaoping Wang

  • Affiliations:
  • Mechanical and Electrical Engineering College, Jiaxing University, Jiaxing, Zhejing, 314001, China;School of Business, Jiaxing University, Jiaxing, Zhejing, 314001, China

  • Venue:
  • International Journal of Computing Science and Mathematics
  • Year:
  • 2013

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Abstract

Copula theory provides a promising solution for the estimation of population probability in estimation distribution algorithms EDAs, and more and more researchers pay attention to copula-EDAs. Most of the copula-EDAs researches are related to two variables case, in this paper, by taking advantage of the ability of pair-copula in high-dimensional correlation construction, a new algorithm is proposed, called pair-copula estimation distribution algorithms pcEDAs. The architecture of pcEDAs is provided, and sampling method of the probability model is discussed, the simulation results based on two different vines, namely C-vine and D-vine, show that the proposed algorithm is not only feasible, but also perform very well.