• DocumentCode
    534216
  • Title

    The Study of Optimizing of Physical Distribution Routing Problem System with Time Windows Based on Genetic Algorithm

  • Author

    Min, Huang ; Zhuo, Wang ; Linghui, Hu

  • Author_Institution
    Coll. of Bus. Adm., Liaoning Tech. Univ., HuLuDao, China
  • Volume
    2
  • fYear
    2010
  • fDate
    16-18 July 2010
  • Firstpage
    59
  • Lastpage
    62
  • Abstract
    With the development of the market economy and improvement of logistics technology professional level, logistics and distribution industry get rapid development. The logistics distribution is a complicated system engineering, which many optimization problems established models and algorithms are very complex, and mostly models and algorithms have NP-hard properties. The paper proceeds theoretical analysis on VRP which is a typical question in logistics distribution optimization. In certain assumptions, we set up mathematical models and gave an outline of genetic algorithm which is a tool of problem solving with global random search ability. Finally, we carry out a series of improvements based on characteristics of genetic algorithm in selection, crossover, mutation and other operations of basic genetic algorithm, and on the basis of realizing a delivery route optimization system.
  • Keywords
    computational complexity; distribution strategy; genetic algorithms; logistics; search problems; NP hard; VRP; distribution industry; genetic algorithm; global random search ability; logistics technology professional level; market economy; optimization; physical distribution routing problem system; time windows; Biological cells; Logistics; Mathematical model; Optimization; Routing; Vehicles; genetic algorithm; logistics and distribution; routing optimization; system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications (IFITA), 2010 International Forum on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-7621-3
  • Electronic_ISBN
    978-1-4244-7622-0
  • Type

    conf

  • DOI
    10.1109/IFITA.2010.74
  • Filename
    5634925