码头桥车自动导引多目标协调优化调度仿真

Multi-Objective Coordination and Optimal Dispatching Simulation of Cranes Automatic Guidance in Container Terminals

针对自动化集装箱码头岸桥和AGV多目标协调建模的复杂性,在考虑集装箱工作优先约束,岸桥距离约束等实际约束的基础上,建立岸桥和AGV双向作业协调调度混合整数模型,目标是最小化岸桥操作的延迟时间和自动导引车的总行驶时间,来提高码头的装卸效率。提出改进的遗传算法(IGA)在合理的计算时间求解建立的模型。通过两组不同规模的算例确定IGA的控制参数及验证IGA的有效性。结果表明,选择合适的交叉和突变率可以获得最优解,IGA可以快速有效地解决岸桥和AGV的协调调度问题。

In order to improve the loading and unloading efficiency of the terminal, against the complexity of the multi-objective coordinated modeling of and automatic guided vehicle （ AGV ）, considering the practical constraints such as container work priority constraint and Qc distance constraint, Qc and AGV bidirectional operation coordinated scheduling mixed integer model is formulated, and the objectives of the model are to minimize the delay time of the QC operations and the total traveling time of the AGVs. Improved genetic algorithm（IGA） was developed to solve the problem in reasonable computational time. The control parameters of IGA were determined and the effectiveness of IGA was verified with two different sizes of examples. The results show that the optimal solution was obtained when choosing suitable crossover and mutation rate, and the IGA can solve the problem of coordinated scheduling of quayside and AGV quickly and effectively.