• DocumentCode
    3660877
  • Title

    An improved social spider algorithm for the Flexible Job-Shop Scheduling Problem

  • Author

    Yao Wang; LinBo Zhu; Jiwen Wang; Jianfeng Qiu

  • Author_Institution
    School of Computer Science and Technology, Anhui University, China
  • fYear
    2015
  • Firstpage
    157
  • Lastpage
    162
  • Abstract
    In this paper, we propose a novel swarm algorithm, called social spider algorithm (SSA), to solve the Flexible Job-Shop Scheduling Problem (FJSP). The SSA algorithm stresses the difference between the two different search agents (spiders): males and females [19]. Some strategies are utilized to generate the initial individual in order to ensure certain quality and diversity, such as global search (GS) and local search (LS) and so on. Moreover, instead of the original SSA algorithm, the improved SSA is combined with the selection, crossover and mutation operation to enhance the performance. The computational result shows that the proposed algorithm produces better results than other authors´ algorithms [23].
  • Keywords
    Support vector machines
  • Publisher
    ieee
  • Conference_Titel
    Estimation, Detection and Information Fusion (ICEDIF), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICEDIF.2015.7280181
  • Filename
    7280181