• DocumentCode
    496126
  • Title

    Study on Hybrid Heuristic Algorithm for Vehicle Routing Problem with Backhauls

  • Author

    Chunyu, Ren ; Jinying, Sun ; Xiaobo, Wang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Heilongjiang Univ., Harbin, China
  • Volume
    1
  • fYear
    2009
  • fDate
    25-26 July 2009
  • Firstpage
    429
  • Lastpage
    432
  • Abstract
    In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; retain the best selection so as to guard the diversity of group. Improved ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as whole. Secondly, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of algorithm. The emulation and calculation proves that it is better than only using genetic algorithm and taboo searching algorithm.
  • Keywords
    convergence; genetic algorithms; mathematical operators; number theory; scheduling; search problems; transportation; vehicles; backhauls model; convergence; customer demand; hybrid genetic heuristic algorithm; natural number coding; optimization; ordinal crossover operator; stock elite; taboo searching algorithm; vehicle scheduling; Algorithm design and analysis; Appraisal; Buildings; Educational institutions; Electronic mail; Genetic algorithms; Heuristic algorithms; Routing; Simulated annealing; Vehicles; VRPB; hybrid genetic algorithm; hybrid heuristic algorithm; taboo searching algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Computer Science, 2009. ITCS 2009. International Conference on
  • Conference_Location
    Kiev
  • Print_ISBN
    978-0-7695-3688-0
  • Type

    conf

  • DOI
    10.1109/ITCS.2009.93
  • Filename
    5190103