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• W2977247718 abstract "The last decade has seen an important role of container terminals in the global trade centers. By another point of view, the high cost of quay cranes on the other hand is a motivation for a set of real-world problems including of Quay Crane Assignment Problem (QCAP) and the Quay Crane Scheduling Problem (QCSP) in the hotspot of research. The main innovation of this proposal is to integrate both QCAP and QCSP to improve Quay Crane (QC) performance by an optimization goal, i.e., QCASP. A real case study in Iran has been applied to validate the proposed problem which has been formulated by a mixed integer linear programming (MILP). Due to inherent complexity of problem proposed in the real-world cases, the Teaching-Learning-Based-Optimization (TLBO) algorithm has been used to find an optimal/global solution in a reasonable time. The applied TLBO has been tuned by Taguchi method and validated in small instances in comparison with an exact method. The computational results show that our proposed TLBO algorithm can solve QCASP, especially in large size instances, successfully. Finally, a set of managerial implications has been recommended to consider the benefits of proposed methodology and algorithm regarding the real case study presented" @default.
• W2977247718 created "2019-10-10" @default.
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• W2977247718 date "2019-08-26" @default.
• W2977247718 modified "2023-09-23" @default.
• W2977247718 title "An Integrated Quay Crane Assignment and Scheduling Problem with Several Contractors in Container Terminals" @default.
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• W2977247718 doi "https://doi.org/10.24200/sci.2019.53338.3191" @default.
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