Conclusions from comparing genetic algorithms for U-shaped assembly line balancing

Alexander Meltser, Yuval Cohen, Mireille Avigal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper compares several different Genetic Algorithm approaches for solving the Mixed Model U-Line Balancing and Sequencing. We first overview the Genetic Algorithms approach and the Assembly Line Balancing Problem in general, then we describe the Mixed Model U-shaped Assembly Line and the problems it presents. We proceed to applications of Genetic Algorithms to these problems, describing and comparing the various algorithms proposed in recent years. Several different algorithms are implemented and the results of comparative executions on benchmark problems follow. The comparisons are done on various combinations of parameter values. In particular, we investigate the behavior of the algorithms under different levels of crossover intensity, mutation intensity and elitism. Finally, we draw conclusions and present potential future research directions.

Original languageEnglish
Title of host publicationIIE Annual Conference and Expo 2014
PublisherInstitute of Industrial Engineers
Number of pages5
ISBN (Electronic)9780983762430
StatePublished - 2014
EventIIE Annual Conference and Expo 2014 - Montreal, Canada
Duration: 31 May 20143 Jun 2014

Publication series

NameIIE Annual Conference and Expo 2014


ConferenceIIE Annual Conference and Expo 2014


  • Assembly line
  • Genetic algorithms
  • Line balancing
  • Mixed model
  • U-line
  • U-shape


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