• DocumentCode
    1594075
  • Title

    An Improved Genetic Algorithm on Logistics Delivery in E-business

  • Author

    Li, Taoshen ; Wu, Jingli

  • Author_Institution
    Guangxi Univ., Nanning
  • Volume
    3
  • fYear
    2007
  • Firstpage
    765
  • Lastpage
    769
  • Abstract
    With the rapid development of e-commerce, logistic industry has also experienced a new reform. Intelligent logistics is an important part of it and plays a key role to realize highly effective logistics. In the process of logistics, there are abundant operational and decision-making problems that need to be solved, and logistic vehicle routing problem is one of which. However, the vehicle routing problem with time windows (VRPTM) is a combination optimization problem and is a NP-complete problem, so we can´t get satisfying results when we use exact approaches and normal heuristic ones. In this paper, an improved genetic algorithm based on RC operator which is an improvement of Route Crossover (RC) is developed to solve the VRPTM. Computational experiments show that this improved algorithm can obtain a general optimality for all evaluated indexes on the premise of satisfying every customer´s demand and its performance is superior to the genetic algorithm based on RC or partially mapped crossover (PMX).
  • Keywords
    electronic commerce; genetic algorithms; logistics; transportation; decision making problems; e-business; e-commerce; improved genetic algorithm; intelligent logistics; logistic industry; logistic vehicle routing problem; logistics delivery; partially mapped crossover; route crossover; vehicle routing problem with time windows; Computer industry; Decision making; Evolution (biology); Evolutionary computation; Genetic algorithms; Logistics; Mathematics; NP-complete problem; Routing; Vehicles; VRPTM; crossover; genetic algorithm; logistics delivery; operator; route crossover (RC);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2007. ICNC 2007. Third International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2875-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2007.211
  • Filename
    4344612