• DocumentCode
    1563392
  • Title

    A Genetic Clustering-Based TCNN Algorithm for Capacity Vehicle Routing Problem

  • Author

    Sun, Huali ; Xie, Jianying ; Xue, Yaofeng

  • Author_Institution
    Dept. of Autom., Shanghai Jiaotong Univ.
  • Volume
    1
  • fYear
    2005
  • Firstpage
    262
  • Lastpage
    265
  • Abstract
    A novel genetic clustering-based transiently chaotic neural network (GCTCNN) algorithm for capacity vehicle routing problem (CVRP) is proposed. CVRP can be partitioned into two kinds of decisions: the selection of vehicles among the available vehicles and the routing of the selected fleet. Using the clustering algorithm the customers are grouped into clusters and each cluster is served by one vehicle. Then transiently chaotic neural network solves the routes to optimality. Computation on benchmark problems and comparison with other known algorithm show that the proposed algorithm produces excellent solutions in short computing times
  • Keywords
    computational complexity; neural nets; pattern clustering; transportation; capacity vehicle routing problem; clustering algorithm; genetic clustering-based transiently chaotic neural network; Chaos; Clustering algorithms; Costs; Genetics; Logistics; Neural networks; Partitioning algorithms; Routing; Sun; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614611
  • Filename
    1614611