Berth Allocation in Container Ports: A Particle Swarm Optimization (PSO)-Based Approach

Management of container ports, with the aim of increasing the efficiency, is considered as a complex problem in coastal transportation engineering. In view of the steadily growing trend of the container ship sizes, more flexible berth allocation planning is mandatory, especially in busy hub ports where ships of various sizes are calling. The berth allocation problem (BAP) in container terminals is defined as berth allocating to the incoming ships so that the total elapsed time of the ships is minimized. The problem is formulated as a mixed integer programming model, assuming that the variables of berthing locations and start times of handling the ships are integers. The assumptions make the model difficult to solve on account of its combinatorial nature. Recently, a genetic algorithm (GA) metaheuristic has been devised for the problem and tested on some test examples. In this paper, a more flexible version of the BAP's mathematical model is considered, in which the variables of berthing locations and start times are real numbers. The goal of this paper is applying the particle swarm optimization (PSO) metaheuristic to this model. An algorithm is implemented and tested by numerical examples, investigating the model's properties and evaluating the PSO against GA. The results showed that the solutions of the problem with real variables of berthing location and start time of ships are enough different from those of the problem with integers. Also, the PSO outperforms the GA in the sense of less computational times.

• Record URL:
  https://doi.org/10.1061/9780784413067.165
• Availability:
  • Find a library where document is available. Order URL: http://www.asce.org/Product.aspx?ID=2147487569&ProductID=192556110
• Supplemental Notes:
  • © 2013 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Joharianzadeh, Mohammad
  • Babazadeh, Abbas
  • Fakher, Ali
• Conference:
  • Ports '13: 13th Triennial International Conference
  • Location: Seattle Washington, United States
  • Date: 2013-8-25 to 2013-8-28
• Publication Date: 2013-8

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1611-1622
• Monograph Title: Ports 2013: Success through Diversification

Subject/Index Terms

• TRT Terms: Berth utilization; Container terminals; Genetic algorithms; Mixed integer programming; Optimization; Port operations
• Uncontrolled Terms: Berth allocation (Ports); Computational time; Particle swarm optimization
• Subject Areas: Marine Transportation; Operations and Traffic Management; Terminals and Facilities; I73: Traffic Control;

Filing Info

• Accession Number: 01521976
• Record Type: Publication
• ISBN: 9780784413067
• Files: TRIS, ASCE
• Created Date: Apr 14 2014 4:35PM