• DocumentCode
    239088
  • Title

    Particle swarm optimization for Integrated Yard Truck Scheduling and Storage Allocation Problem

  • Author

    Niu, Ben ; Xie, T. ; Duan, Q.Q. ; Tan, L.J.

  • Author_Institution
    Coll. of Manage., Shenzhen Univ., Shenzhen, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    634
  • Lastpage
    639
  • Abstract
    The Integrated Yard Truck Scheduling and Storage Allocation Problem (YTS-SAP) is one of the major optimization problems in container port which minimizes the total delay for all containers. To deal with this NP-hard scheduling problem, standard particle swarm optimization (SPSO) and a local version PSO (LPSO) are developed to obtain the optimal solutions. In addition, a simple and effective `problem mapping´ mechanism is used to convert particle position vector into scheduling solution. To evaluate the performance of the proposed approaches, experiments are conducted on different scale instances to compare the results obtained by GA. The experimental studies show that PSOs outperform GA in terms of computation time and solution quality.
  • Keywords
    genetic algorithms; particle swarm optimisation; scheduling; sea ports; storage; LPSO; NP-hard scheduling problem; SPSO; YTS-SAP; container port; integrated yard truck scheduling and storage allocation problem; local version PSO; particle position vector; problem mapping mechanism; standard particle swarm optimization; total delay minimization; Containers; Delays; Genetic algorithms; Job shop scheduling; Loading; Resource management; Yttrium; Container terminal; Particle Swarm Optimization (PSO); Storage allocation; Yard truck scheduling;
  • 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.2014.6900480
  • Filename
    6900480