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Combined quay crane assignment and quay crane scheduling with crane inter-vessel movement and non-interference constraints

Author

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  • Ghazwan Alsoufi
  • Xinan Yang
  • Abdellah Salhi

Abstract

Integrated models of the quay crane assignment problem (QCAP) and the quay crane scheduling problem (QCSP) exist. However, they have shortcomings in that some do not allow movement of quay cranes between vessels, others do not take into account precedence relationships between tasks, and yet others do not avoid interference between quay cranes. Here, an integrated and comprehensive optimization model that combines the two distinct QCAP and QCSP problems which deals with the issues raised is put forward. The model is of the mixed-integer programming type with the objective being to minimize the difference between tardiness cost and earliness income based on finishing time and requested departure time for a vessel. Because of the extent of the model and the potential for even small problems to lead to large instances, exact methods can be prohibitive in computational time. For this reason an adapted genetic algorithm (GA) is implemented to cope with this computational burden. Experimental results obtained with branch-and-cut as implemented in CPLEX and GA for small to large-scale problem instances are presented. The paper also includes a review of the relevant literature.

Suggested Citation

  • Ghazwan Alsoufi & Xinan Yang & Abdellah Salhi, 2018. "Combined quay crane assignment and quay crane scheduling with crane inter-vessel movement and non-interference constraints," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(3), pages 372-383, March.
    • Handle: RePEc:taf:tjorxx:v:69:y:2018:i:3:p:372-383
    DOI: 10.1057/s41274-017-0226-3
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    Cited by:

    1. Chargui, Kaoutar & Zouadi, Tarik & Sreedharan, V. Raja & El Fallahi, Abdellah & Reghioui, Mohamed, 2023. "A novel robust exact decomposition algorithm for berth and quay crane allocation and scheduling problem considering uncertainty and energy efficiency," Omega, Elsevier, vol. 118(C).
    2. 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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