• DocumentCode
    2957978
  • Title

    The Simultaneous Quay Crane and Truck Scheduling Problem in Container Terminals

  • Author

    Zhao, Jiao ; Tang, Lixin

  • Author_Institution
    Liaoning Key Lab. of Manuf. Syst. & Logistics, Northeastern Univ., Shenyang, China
  • Volume
    1
  • fYear
    2011
  • fDate
    28-29 March 2011
  • Firstpage
    279
  • Lastpage
    282
  • Abstract
    This paper addresses the simultaneous quay crane and truck scheduling problem (QC&TSP) at a container terminal. This paper considers one quay crane and several trucks to unload containers from the vessel, and every truck needs some time to come back to the quay crane after transports one container to the yard, then it can transport another container continually. In this paper, every container is arranged as a task to unload separately. Based on the features of the scheduling problem, an improved PSO (Particle Swarms Optimization) algorithm is presented to solve the scheduling problem, which develops a new formulation for updating velocity, besides, the decode method of the particles is designed in particular. Experiments are carried out especially to evaluate the performance of the proposed PSO algorithm, and compare with the solutions obtained by CPLEX software. The results show that the proposed PSO algorithm is efficient for solving the problem in the solution quality and computation time.
  • Keywords
    cranes; particle swarm optimisation; scheduling; sea ports; transportation; CPLEX software; container terminals; particle swarm optimization; simultaneous quay crane; transportation; truck scheduling problem; Algorithm design and analysis; Containers; Cranes; Job shop scheduling; Processor scheduling; Routing; Software algorithms; container terminals; quay crane; scheduling; truck;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
  • Conference_Location
    Shenzhen, Guangdong
  • Print_ISBN
    978-1-61284-289-9
  • Type

    conf

  • DOI
    10.1109/ICICTA.2011.80
  • Filename
    5750610