首页|Optimal Model and Algorithm Design for the Multi-Equipment Resource Collaborative Scheduling of Automated Terminals Considering the Mixing Process

Optimal Model and Algorithm Design for the Multi-Equipment Resource Collaborative Scheduling of Automated Terminals Considering the Mixing Process

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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.

Automated terminalCollaborative schedulingHybrid processSimulated annealing particle swarm algorithmUncertaintyScheduling Solutions

Liangyong Chu、Dong Liang、Yupei Zhou、Jiawen Zhang

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Modern Logistics Research Center,Jimei University,Xiamen 361021,China

国家重点研发计划福建省自然科学基金Department of Education of Fujian Province ProjectDepartment of Education of Fujian Province Project

2017YFC08053092021J01820JAT190294JAT210230

2024

10.1007/s11804-024-00412-7

哈尔滨工程大学学报(英文版)
哈尔滨工程大学

哈尔滨工程大学学报(英文版)

CSTPCD
影响因子：0.381
ISSN：1671-9433
年,卷(期)：2024.23(2)
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