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Modeling and solution of the joint quay crane and truck scheduling problem

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  • Tang, Lixin
  • Zhao, Jiao
  • Liu, Jiyin

Abstract

This paper addresses the joint quay crane and truck scheduling problem at a container terminal, considering the coordination of the two types of equipment to reduce their idle time between performing two successive tasks. For the unidirectional flow problem with only inbound containers, in which trucks go back to quayside without carrying outbound containers, a mixed-integer linear programming model is formulated to minimize the makespan. Several valid inequalities and a property of the optimal solutions for the problem are derived, and two lower bounds are obtained. An improved Particle Swarm Optimization (PSO) algorithm is then developed to solve this problem, in which a new velocity updating strategy is incorporated to improve the solution quality. For small sized problems, we have compared the solutions of the proposed PSO with the optimal solutions obtained by solving the model using the CPLEX software. The solutions of the proposed PSO for large sized problems are compared to the two lower bounds because CPLEX could not solve the problem optimally in reasonable time. For the more general situation considering both inbound and outbound containers, trucks may go back to quayside with outbound containers. The model is extended to handle this problem with bidirectional flow. Experiment shows that the improved PSO proposed in this paper is efficient to solve the joint quay crane and truck scheduling problem.

Suggested Citation

  • Tang, Lixin & Zhao, Jiao & Liu, Jiyin, 2014. "Modeling and solution of the joint quay crane and truck scheduling problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 978-990.
    • Handle: RePEc:eee:ejores:v:236:y:2014:i:3:p:978-990
    DOI: 10.1016/j.ejor.2013.08.050
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    15. Boysen, Nils & Briskorn, Dirk & Meisel, Frank, 2017. "A generalized classification scheme for crane scheduling with interference," European Journal of Operational Research, Elsevier, vol. 258(1), pages 343-357.
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    22. Raeesi, Ramin & Sahebjamnia, Navid & Mansouri, S. Afshin, 2023. "The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions," European Journal of Operational Research, Elsevier, vol. 310(3), pages 943-973.
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