Rational genetic algorithm and its application to the problem of motion planning

Xingjian Jing, Yue Chao Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

By using the feedback of genetic informatione, a rational genetic algorithm (RGA) is proposed to overcome the drawbacks of conventional genetic algorithms such as slow convergence. The genetic information (GI) is extended in order to improve its completeness, and the rational genetic operators are rebuilt with more generality based on the extended GI. A more general specification for the whole RGA is given and the global convergence of the RGA is shown. Theoretical analysis and practical application to motion planning are given to illustrate the effectiveness of RGA.
Original languageEnglish
Pages (from-to)1017-1021
Number of pages5
JournalKongzhi yu Juece/Control and Decision
Volume19
Issue number9
Publication statusPublished - 1 Sep 2004
Externally publishedYes

Keywords

  • Genetic information
  • Motion planning
  • Rational genetic algorithm (RGA)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Control and Optimization
  • Artificial Intelligence

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