Assembly line balancing based on double chromosome genetic algorithm

Yanhou Liu, Dunwen Zuo, Dan Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Aiming at assembly line balancing problem, a double chromosome genetic algorithm (DCGA) is proposed to avoid trapping in local optimum, which is a disadvantage of standard genetic algorithm (SGA). In this algorithm, there are two chromosomes of each individual, and the better one, regarded as dominant chromosome, determines the fitness. Dominant chromosome keeps excellent gene segments to speed up the convergence, and recessive chromosome maintains population diversity to get better global search ability to avoid local optimal solution. When the amounts of chromosomes are equal, the population size of DCGA is half that of SGA, which significantly reduces evolutionary time. Finally, the effectiveness is verified by experiments.

Original languageEnglish
Pages (from-to)622-628
Number of pages7
JournalTransactions of Nanjing University of Aeronautics and Astronautics
Volume31
Issue number6
Publication statusPublished - 1 Dec 2014
Externally publishedYes

Keywords

  • Assembly line balancing
  • Double chromosome
  • Genetic algorithm
  • Global optimum
  • Mathematical model

ASJC Scopus subject areas

  • Aerospace Engineering
  • Space and Planetary Science

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