Optimisation for Quay Crane Scheduling Problem under Uncertainty using PSO and OCBA

This paper addresses the quay crane scheduling problem (QCSP) under uncertain conditions at container terminals. Variations in container volume, arrival time, equipment functionality and weather conditions create significant uncertainties when scheduling loading and unloading tasks. In order to maintain the service level of the port under various conditions, port operator urgently need to execute a robust schedule. In this paper, a stochastic programming model is formulated to minimise the makespan of quay crane service, using a particle swarm optimisation (PSO) algorithm integrated with optimal computing budget allocation (OCBA) to improve computational efficiency. Numerical experiments show that the applied algorithm performs well under uncertainty.

• Record URL:
  • https://doi.org/10.1504/IJSTL.2019.099274
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/17566517
• Supplemental Notes:
  • Copyright © 2018 Inderscience Enterprises Ltd.
• Authors:
  • Hu, Hongtao
  • Chen, Xiazhong
  • Zhang, Si
• Publication Date: 2019

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 196-215
• Serial:
  • International Journal of Shipping and Transport Logistics
  • Volume: 11
  • Issue Number: 2-3
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1756-6517
  • EISSN: 1756-6525
  • Serial URL: http://www.inderscience.com/jhome.php?jcode=ijstl

Subject/Index Terms

• TRT Terms: Container terminals; Loading and unloading; Optimization; Scheduling; Stochastic programming; Uncertainty
• Uncontrolled Terms: Particle swarm optimization
• Subject Areas: Freight Transportation; Marine Transportation; Operations and Traffic Management;

Filing Info

• Accession Number: 01709080
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 27 2019 2:41PM