Adaptive chaos hybrid multi-objective genetic algorithm based on the Tent map

Rui Nie, Weiguo Zhang, Guangwen Li, Xiaoxiong Liu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

A modified algorithm which realized the tent map on the computer was proposed to deal effectively with the problem of fixed point and the small periodic of the tent map, which affected by the finite word-length of computer. The chaos research algorithm based on the modified Tent map was introduced to the multi-objective genetic algorithm. Firstly, the chaos sequence was applied to assign the initial population value to enhance the convergence ability. Then, the chaos search optimization algorithm was adopted to improve the diversity of the population. The benchmark problems were tested by the basic and the modified algorithm respectively. The statistical results show that the improved algorithm could seek the solution more efficiently, and achieve better convergence and diversity than basic NSGA-II.

Original languageEnglish
Pages (from-to)1010-1016
Number of pages7
JournalBeijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
Volume38
Issue number8
StatePublished - Aug 2012

Keywords

  • Chaos
  • Generation gap distance index
  • Genetic algorithm
  • Multi-objective optimization
  • Tent map

Fingerprint

Dive into the research topics of 'Adaptive chaos hybrid multi-objective genetic algorithm based on the Tent map'. Together they form a unique fingerprint.

Cite this