• DocumentCode
    2227133
  • Title

    A species based multiobjective evolutionary algorithm for multiobjective flow shop scheduling problem

  • Author

    Wang, Hongfeng ; Fu, Yaping ; Huang, Min

  • Author_Institution
    College of Information Science and Engineering, Northeastern University; State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University; Shenyang, P.R. China
  • fYear
    2015
  • fDate
    25-28 May 2015
  • Firstpage
    3243
  • Lastpage
    3247
  • Abstract
    In recent years, multiobjective scheduling problems (MOSPs) have gained more and more concerns since many real-world applications always involve in multiple different objectives. In this paper, a multiobjective flow shop scheduling problem is investigated and a species based multiobjective evolutionary algorithm (MOEA), where a new multipopulation scheme is designed based on the mechanism of species that was used in EA for multimodal optimization problems, is proposed as its solution algorithm. Extensive experiments are carried out on a set of randomly-generated test problems in order to examine strongness and weakness of the performance of the proposed MOEA through comparing with two well-known MOEAs for addressing MOSPs.
  • Keywords
    Algorithm design and analysis; Evolutionary computation; Job shop scheduling; Optimization; Sociology; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2015 IEEE Congress on
  • Conference_Location
    Sendai, Japan
  • Type

    conf

  • DOI
    10.1109/CEC.2015.7257295
  • Filename
    7257295