Rational genetic algorithm and its application to motion cooperation of multiple mobile robots

Xingjian Jing, Yue Chao Wang, Da Long Tan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

When conventional genetic algorithm (GA) is used to cope with some complex problems, slow convergence or prematurity often occurs. A novel evolutionary algorithm, based on the rational decision-making of human, the rational genetic algorithm (RGA) is proposed to solve these problems. The key point of RGA is to use the genetic information feedback and set up rational rules to guide the evolution of genetic individuals. The proposed RGA effectively incorporates inheriting and learning behaviors of knowledge and experiences of species into GA. The problem of multi-robot motion cooperation under known circumstance can be solved better by RGA than conventional GA. Theoretical analysis and simulation results show the validity of RGA.
Original languageEnglish
Pages (from-to)955-961
Number of pages7
JournalZidonghua Xuebao/Acta Automatica Sinica
Volume28
Issue number6
Publication statusPublished - 1 Nov 2002
Externally publishedYes

Keywords

  • Genetic information
  • Multi-robot motion cooperation
  • Rational decision-making principle
  • Rational rules

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Computer Graphics and Computer-Aided Design

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