• DocumentCode
    1609570
  • Title

    Autonomous Distributed Genetic Approach for Route Planning Problems

  • Author

    Noishiki, M. ; Sakakibara, K. ; Nishikawa, I. ; Tamaki, H. ; Nakayama, K.

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Ritsumeikan Univ., Kusatsu
  • fYear
    2006
  • Firstpage
    6075
  • Lastpage
    6079
  • Abstract
    We consider the pickup and delivery problem with time windows as a general model of the practical transportation problems in automated guided vehicle systems, logistic systems, etc. The problem requires that any paired pickup and delivery locations have to be served by one vehicle and the pickup location has to be scheduled before the corresponding delivery location in the route. In this paper, to search a set of routes close to the optimal one, we propose the autonomous distributed genetic approach based on the search space decomposition for the problem. In this approach, first, the search space is divided into sub-spaces based on the number of customers loaded in each vehicle. Then, GA is applied in each sub-space. In addition, the dynamic separation is applied for an efficient search. The effectiveness of the search space decomposition is evaluated by computational experiments
  • Keywords
    genetic algorithms; search problems; transportation; automated guided vehicle system; autonomous distributed genetic approach; logistic system; route planning problem; search space decomposition; time window-based pickup and delivery problem; transportation problem; Educational institutions; Electronic mail; Genetic algorithms; Genetic engineering; Information science; Logistics; Remotely operated vehicles; Space vehicles; Transportation; Vehicle dynamics; dynamic separation; genetic algorithm; pickup and delivery problem; search space decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE-ICASE, 2006. International Joint Conference
  • Conference_Location
    Busan
  • Print_ISBN
    89-950038-4-7
  • Electronic_ISBN
    89-950038-5-5
  • Type

    conf

  • DOI
    10.1109/SICE.2006.315210
  • Filename
    4108667