基于差分进化算法的自动化集装箱码头AGV调度问题

AGV Scheduling in Automated Container Terminal Based on Differential Evolution Algorithm

【目的】自动化集装箱码头的水平运输作业是影响港口物流效率的关键环节,通过优化自动导引车(Automated guided vehicle,AGV)的任务分配,减少装卸作业的时间,提高港口生产效率。【方法】在同时考虑集装箱装卸作业的基础上,就AGV调度问题建立混合整数规划(MIP)模型,优化目标为极小化岸桥完工时间。考虑到该问题具有NP困难性,设计了离散差分进化(DDE)算法进行近似求解。【结果】通过数值仿真验证了MIP模型和DDE算法的有效性。【结论】结果表明上述模型和算法可以为自动化集装箱码头的装卸作业提供帮助。

[Purposes]Automated guided vehicle(AGV)is the horizontal transportation equipment of the automated container terminal.The optimization of AGVs’scheduling can save the time of loading and unloading operations and improve the terminal production efficiency.[Methods]It establishes a mixed integer programming(MIP)model with the objective to minimize the makespan of quay crane given loading and unloading operations simultaneously and the container operation sequence in horizontal transportation of automated container terminal.For this NP-hard problem,a differential evolution algorithm is designed to handle the problem.[Findings]Numerical simulations are conducted to show the effectiveness of the proposed MIP model and algorithm.[Conclusions]The results show that the model and algorithm can provide help for the scheduling of loading and unloading operations in container terminal.