RasID-GA with Simplex Crossover(SPX) for optimization problems

Dong Kyu Sohn, Shingo Mabu, Kotaro Hirasawa, Jinglu Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose RasID-GA (an abbreviation of Adaptive Random Search with Intensification and Diversification combined with Genetic Algorithm) which improves the ability of diversification searching with Simplex Crossover (SPX). SPX generates the offspring based on uniform probability distribution and uses the M + 1 number of parent vectors, where M is the dimension of the vector. The RasIDGA with Simplex Crossover is compared with parallel RasIDs and GA with Simplex Crossover using 23 different objective functions having no local minima, a small number of local minima and a large number of local minima.

Original languageEnglish
Title of host publication2006 IEEE Congress on Evolutionary Computation, CEC 2006
Pages3021-3028
Number of pages8
Publication statusPublished - 2006 Dec 1
Event2006 IEEE Congress on Evolutionary Computation, CEC 2006 - Vancouver, BC, Canada
Duration: 2006 Jul 162006 Jul 21

Publication series

Name2006 IEEE Congress on Evolutionary Computation, CEC 2006

Conference

Conference2006 IEEE Congress on Evolutionary Computation, CEC 2006
CountryCanada
CityVancouver, BC
Period06/7/1606/7/21

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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  • Cite this

    Sohn, D. K., Mabu, S., Hirasawa, K., & Hu, J. (2006). RasID-GA with Simplex Crossover(SPX) for optimization problems. In 2006 IEEE Congress on Evolutionary Computation, CEC 2006 (pp. 3021-3028). [1688690] (2006 IEEE Congress on Evolutionary Computation, CEC 2006).