• DocumentCode
    239421
  • Title

    Locality-sensitive hashing based multiobjective memetic algorithm for dynamic pickup and delivery problems

  • Author

    Fangxiao Wang ; Yuan Gao ; Zexuan Zhu

  • Author_Institution
    Coll. of Comput. Sci. & Software Eng., Shenzhen Univ., Shenzhen, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    661
  • Lastpage
    666
  • Abstract
    This paper proposes a locality-sensitive hashing based multiobjective memetic algorithm namely LSH-MOMA for solving pickup and delivery problems with dynamic requests (DPDPs for short). Particularly, LSH-MOMA is designed to find the solution route of a DPDP by optimizing objectives namely workload and route length in an evolutionary manner. In each generation of LSH-MOMA, locality-sensitive hashing based rectification and local search are imposed to repair and refine the individual candidate routes. LSH-MOMA is evaluated on three simulated DPDPs of different scales and the experimental results demonstrate the efficiency of the method.
  • Keywords
    genetic algorithms; vehicle routing; DPDP with dynamic requests; LSH-MOMA algorithm; dynamic pickup-and-delivery problems; locality-sensitive hashing based multiobjective memetic algorithm; route length objective; workload objective; Biological cells; Heuristic algorithms; Lattices; Sociology; Statistics; Vehicle dynamics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2014 IEEE Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6626-4
  • Type

    conf

  • DOI
    10.1109/CEC.2014.6900653
  • Filename
    6900653