Scheduling optimization of quay crane operation in container terminal considering container relocation in yard

Jun Ma

doi:10.1117/12.2683849

14 June 2023 Scheduling optimization of quay crane operation in container terminal considering container relocation in yard

Jun Ma

Author Affiliations +

Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）; 127082M (2023) https://doi.org/10.1117/12.2683849
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 2023, Chongqing, China

Abstract

In order to improve the efficiency of handling operations at a certain bay on a ship in a container terminal, the operation sequence optimization of quay crane and yard crane is studied under the condition of considering the storage in the yard. Using linear programming method of operational research, a mixed integer programming model is established to minimize the operation time of quay crane and give the operation sequence of the quay crane. A mathematical example is designed to compare with the dual-cycle operation strategy that usually does not consider the container relocation operation in the yard. In addition, the sensitivity of the model is analysed to verify the results of the model under different scenarios. The experimental results show that the dual-cycle operation strategy considering relocation in yard some-times has less dual cycle times but shorter total working time than the dual-cycle operation strategy without considering relocation in yard, which verifies its necessity. And while optimizing the operation sequence, it can give suggestions on the operation of the yard, indicating that the constructed model can better handle the optimization problem of the quay crane operation considering container relocation in yard.

Citation Download Citation

Jun Ma "Scheduling optimization of quay crane operation in container terminal considering container relocation in yard", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 127082M (14 June 2023); https://doi.org/10.1117/12.2683849

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