郭子坚Guo Zijian

(教授)

 博士生导师  硕士生导师
学位:博士
性别:男
毕业院校:日本大学大学院
所在单位:水利工程系
电子邮箱:zjguo@dlut.edu.cn

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基于多智能体仿真的集装箱港口作业效率研究

发表时间:2023-02-24 点击次数:

论文名称:基于多智能体仿真的集装箱港口作业效率研究
发表刊物:水运工程
期号:9
页面范围:83-87,93
ISSN号:1002-4972
摘要:Container terminal operation system is a complex discrete-event system, whose characteristics are difficult to be described by mathematical models, while process-based simulation models are in lack of flexibility of equipment dispatching.In order to analyze the effect of the yard truck fleet size on terminal operational performance by precisely depicting the container flows at port, an event-driven multi-agent simulation model for domestic container terminals is proposed.Results indicate that, gross crane rate ( GCR) first increases steeply and then slowly as the number of yard truck increases, and both average waiting time ( AWT) and average service time ( AST) of ships show high negative correlations with GCR.
备注:新增回溯数据
发表时间:2022-10-10