• DocumentCode
    3262736
  • Title

    Parallel genetic algorithm for periodic vehicle routing and scheduling problem

  • Author

    Kurdel, P. ; Sebestyenova, J.

  • Author_Institution
    Inst. of Inf., Bratislava, Slovakia
  • fYear
    2013
  • fDate
    4-6 July 2013
  • Firstpage
    111
  • Lastpage
    116
  • Abstract
    The consideration of environmental costs is essentially changing the transportation policy in developed countries. The reduction in total distance travelled will in itself provide environmental benefits due to the reduction in fuel consumed and in the resulting pollutants. The cash deployment strategy for a network of ATMs should take into account the analysis of inventory policies, logistics costs as well as of the routing of replenishment vehicles. The optimal strategy has to focus on the reduction of cash-related expenses while safeguarding that ATMs do not run out of cash. The problem, which can be tackled as a kind of rich vehicle routing problem is in the paper solved using parallel genetic algorithm. The proposed model is able to solve cases with simultaneous requirements of several replenishments for some of the customers (ATMs) daily and a single replenishment in several days for other groups of customers.
  • Keywords
    genetic algorithms; parallel algorithms; scheduling; vehicle routing; ATM; cash deployment strategy; environmental costs; fuel consumption; inventory policies; parallel genetic algorithm; periodic scheduling problem; periodic vehicle routing; transportation policy; Biological cells; Genetic algorithms; Optimization; Planning; Roads; Routing; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Science and Engineering (ICSSE), 2013 International Conference on
  • Conference_Location
    Budapest
  • ISSN
    2325-0909
  • Print_ISBN
    978-1-4799-0007-7
  • Type

    conf

  • DOI
    10.1109/ICSSE.2013.6614643
  • Filename
    6614643