Int J Performability Eng ›› 2017, Vol. 13 ›› Issue (7): 1020-1029.doi: 10.23940/ijpe.17.07.p3.10201029

• Original articles • Previous Articles     Next Articles

A Variable Neighborhood Migrating Birds Optimization Algorithm for Flexible Job Shop Scheduling

Hongchan Lia, Bangqin Caob, and Haodong Zhua, *   

  1. aSchool of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, 450002, China
    bXinyang Vocational and Technical College, Xinyang, Henan, 464000, China

Abstract: A hybrid meta-heuristic named variable neighborhood migrating birds optimization (VNMBO), which is a combination of variable neighborhood search (VNS) and migrating birds optimization (MBO). The main aim of this paper is to provide a new way for MBO to solve the flexible job shop scheduling problem (FJSP). A two-stage population initialization scheme was first adopted to improve the quality of the initial solutions. An individual leaping mechanism was introduced to the algorithm in order to avoid the premature convergence. To search the solution space effectively, three neighborhood structures were designed and a VNS was developed to enhance the local searching ability. Finally, to assess the performance of the proposed VNMBO, some published algorithms were compared by using two famous benchmark data sets. The comparison results show that the proposed VNMBO is effective for solving the FJSP with the objective of minimizing the makespan.

Submitted on July 24, 2017; Revised on October 13, 2017; Accepted on October 21, 2017
References: 19