• DocumentCode
    2466388
  • Title

    Improved Genetic Algorithm Research for Route Optimization of Logistic Distribution

  • Author

    Bin, Xiao ; Min, Wang ; Yanming, Liu ; Yu, Fang

  • Author_Institution
    Sch. of Comput. Sci., Southwest Pet. Univeristy, Chengdu, China
  • fYear
    2010
  • fDate
    17-19 Dec. 2010
  • Firstpage
    1087
  • Lastpage
    1090
  • Abstract
    This paper aims at GA´s weakness and shortage of neighborhood search capability, proposed 3-opt based mutation operator, sub-path communicating operator and dynamic switching mutation of dual-point operator. The simulation results illustrate that the neighborhood search capability could be improved by this operator and the relatively steady solution could be gained as well. Hence, the research and modeling have been achieved for the issues of logistic distribution route which is ubiquitous in practical application of distribution central with various vehicles. By applying advanced GA to solve the issues, the simulation result shows that the improved GA is efficient when solving the problems of distributing routes within multiple distribution centrals with multiple vehicle types.
  • Keywords
    genetic algorithms; goods distribution; logistics; dual-point operator; genetic algorithm; logistic distribution; mutation operator; neighborhood search capability; route optimization; sub-path communicating operator; Biological cells; Gallium; Logistics; Optimization; Switches; Vehicle dynamics; Vehicles; distributing route problem; dynamic switching mutation operator; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational and Information Sciences (ICCIS), 2010 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-8814-8
  • Electronic_ISBN
    978-0-7695-4270-6
  • Type

    conf

  • DOI
    10.1109/ICCIS.2010.269
  • Filename
    5709450