A Three-Dimensional Encoding Genetic Algorithm for Job Shop Scheduling

  • Authors:
  • Hongli Yin;Yongming Wang;Nanfeng Xiao;Enliang Hu;Yanrong Jiang

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • CISW '07 Proceedings of the 2007 International Conference on Computational Intelligence and Security Workshops
  • Year:
  • 2007

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Abstract

In so many combinatorial optimization problems, Job shop scheduling problems have earned a reputation for being difficult to solve. GA has demonstrated considerable success in providing efficient solutions to many non-polynomial-hard optimization problems. In the field of job shop scheduling, GA has been intensively researched, and there are nine kinds of methods were proposed to encoding chromosome to represent a solution. In this paper, we proposed a novel genetic chromosome encoding approach, in this encoding method, the operation of crossover and mutation was done in three-dimensional coded space. 5 selected benchmark problems were tried with the proposed three- dimensional encoding GA for validation and the results are encouraging.