Genetic Symbiosis Algorithm

K. Hirasawa, Y. Ishikawa, J. Hu, J. Murata, J. Mao

Research output: Contribution to conferencePaper

13 Citations (Scopus)

Abstract

In this paper, a new Genetic Symbiosis Algorithm (GSA) is proposed based on the symbiotic concept found widely in ecosystems. Since in the conventional Genetic Algorithms (GA) reproduction is done using only the fitness function of each individual, there are some problems such as premature convergence to an undesirable solution at a very early stage of generation. In addition in some GA applications, it is sometimes required to maintain diversified solutions and to find out many locally optimal solutions. GSA is proposed to solve these problems by considering mutual symbiotic relations between Individuals. From simulations on optimizing a nonlinear function, it has been clarified that GSA can find more flexible solutions that can meet a variety of user's requests than the conventional methods.

Original languageEnglish
Pages1377-1384
Number of pages8
Publication statusPublished - 2000 Dec 3
Externally publishedYes
EventProceedings of the 2000 Congress on Evolutionary Computation - California, CA, USA
Duration: 2000 Jul 162000 Jul 19

Other

OtherProceedings of the 2000 Congress on Evolutionary Computation
CityCalifornia, CA, USA
Period00/7/1600/7/19

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)
  • Computational Theory and Mathematics

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  • Cite this

    Hirasawa, K., Ishikawa, Y., Hu, J., Murata, J., & Mao, J. (2000). Genetic Symbiosis Algorithm. 1377-1384. Paper presented at Proceedings of the 2000 Congress on Evolutionary Computation, California, CA, USA, .