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Citation:
　Liangyong Chu,Dong Liang,Yupei Zhou,et al.Optimal Model and Algorithm Design for the Multi-Equipment Resource Collaborative Scheduling of Automated Terminals Considering the Mixing Process[J].Journal of Marine Science and Application,2024,(2):479-490.[doi:10.1007/s11804-024-00412-7]
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Optimal Model and Algorithm Design for the Multi-Equipment Resource Collaborative Scheduling of Automated Terminals Considering the Mixing Process

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Title:
Optimal Model and Algorithm Design for the Multi-Equipment Resource Collaborative Scheduling of Automated Terminals Considering the Mixing Process
Author(s):
Liangyong Chu;  Dong Liang;  Yupei Zhou;  Jiawen Zhang
Affilations:
Author(s):
Liangyong Chu;  Dong Liang;  Yupei Zhou;  Jiawen Zhang
Modern Logistics Research Center, Jimei University, Xiamen 361021, Chin
Keywords:
Automated terminal|Collaborative scheduling|Hybrid process|Simulated annealing particle swarm algorithm|Uncertainty|Scheduling Solutions
分类号:
-
DOI:
10.1007/s11804-024-00412-7
Abstract:
Considering the uncertainty of the speed of horizontal transportation equipment, a cooperative scheduling model of multiple equipment resources in the automated container terminal was constructed to minimize the completion time, thus improving the loading and unloading efficiencies of automated container terminals. The proposed model integrated the two loading and unloading processes of "double-trolley quay crane + AGV + ARMG" and "single-trolley quay crane + container truck + ARMG" and then designed the simulated annealing particle swarm algorithm to solve the model. By comparing the results of the particle swarm algorithm and genetic algorithm, the algorithm designed in this paper could effectively improve the global and local space search capability of finding the optimal solution. Furthermore, the results showed that the proposed method of collaborative scheduling of multiple equipment resources in automated terminals considering hybrid processes effectively improved the loading and unloading efficiencies of automated container terminals. The findings of this study provide a reference for the improvement of loading and unloading processes as well as coordinated scheduling in automated terminals.

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Memo

Memo:
Received date: 2023-03-13;Accepted date: 2023-06-25。
Foundation item: This work is supported by the National Key R&D Program of China (Grant No.2017YFC0805309),Natural Science Foundation of Fujian Province (Grant No.2021J01820),and Department of Education of Fujian Province Project (Grant Nos.JAT190294 and JAT210230).
Corresponding author: Liangyong Chu,E-mail:chuliangyong@163.com
Last Update: 2024-05-28