Quantitative analysis and prevention of genetic algorithm premature convergence

Min Le Wang, Xiao Guang Gao, Gang Liu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

To aim at the problem of genetic algorithm premature convergence, the new definition of premature convergence is given, and a new fuzzy index for measuring population maturity degree is presented on the basis of fuzzy system theory. Finally, the method of adaptively adjusting crossover probability and mutation probability with population maturity degree is proposed to prevent premature convergence, and its validity is verified through a simulation experiment.

Original languageEnglish
Pages (from-to)1249-1251+1288
JournalXi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Volume28
Issue number8
StatePublished - Aug 2006

Keywords

  • Adaptive control
  • Fuzzy system theory
  • Genetic algorithm
  • Premature convergence

Fingerprint

Dive into the research topics of 'Quantitative analysis and prevention of genetic algorithm premature convergence'. Together they form a unique fingerprint.

Cite this