An efficient memetic algorithm for solving the job shop scheduling problem

  • Authors:

  • Liang Gao;Guohui Zhang;Liping Zhang;Xinyu Li

  • Affiliations:

  • The State Key Laboratory of Digital Manufacturing Equipment and Technology, 1037 Luoyu Road, Huazhong University of Science & Technology, Wuhan 430074, China;Zhengzhou Institute of Aeronautical Industry Management, Middle Daxue Road, Zhengzhou 450015, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, 1037 Luoyu Road, Huazhong University of Science & Technology, Wuhan 430074, China;The State Key Laboratory of Digital Manufacturing Equipment and Technology, 1037 Luoyu Road, Huazhong University of Science & Technology, Wuhan 430074, China

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2011

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Abstract

The job shop scheduling problem (JSP) is well known as one of the most complicated combinatorial optimization problems, and it is a NP-hard problem. Memetic algorithm (MA) which combines the global search and local search is a hybrid evolutionary algorithm. In this paper, an efficient MA with a novel local search is proposed to solve the JSP. Within the local search, a systematic change of the neighborhood is carried out to avoid trapping into local optimal. And two neighborhood structures are designed by exchanging and inserting based on the critical path. The objective of minimizing makespan is considered while satisfying a number of hard constraints. The computational results obtained in experiments demonstrate that the efficiency of the proposed MA is significantly superior to the other reported approaches in the literature.