• DocumentCode
    1896837
  • Title

    Study on Hybrid Genetic Algorithm for Multi-type Vehicles and Multi-depot Vehicle Routing Problem with Backhauls

  • Author

    Chunyu, Ren ; Xiaobo, Wang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Heilongjiang Univ. Harbin, Harbin, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    197
  • Lastpage
    200
  • Abstract
    Multi-type vehicles and multi-depot vehicle routing problem with backhauls (MVMDVRPB) has been paid more attentions. According to the characteristics of model, hybrid genetic algorithm is used to get the optimization solution. First of all, use hybrid coding so as to simplify the problem; construct the pertinence of initial solution to enhance the feasibility of solutions; retain the best selection so as to guard the diversity of group. Improved partially matched crossover operators can avoid destroying good gene parts during the course of crossover. The study adopts 2- exchange mutation operator, combine hill-climbing algorithm to strengthen the partial searching ability of chromosome. This algorithm can offer the thought to settle the practical problem in scale. At the same time, it can be known that adopting hybrid picking-delivery strategy can save the distance of distribution route so as to improve economic benefit.
  • Keywords
    genetic algorithms; mathematical operators; search problems; transportation; vehicles; 2-exchange mutation operator; MVMDVRPB; backhaul; hill-climbing algorithm; hybrid genetic algorithm; multidepot vehicle routing problem; multitype vehicle routing problem; optimization; picking-delivery strategy; search problem; transportation; Automation; Biological cells; Genetic algorithms; Genetic mutations; Heuristic algorithms; Information science; Intelligent vehicles; Optimization methods; Routing; Transportation; Multi-type vehicles; hybrid genetic algorithm; multi-depot; vehicle routing problem with backhauls;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.56
  • Filename
    5287674