Abstract:

In order to solve the coordination problem of multi-stage equipment operation on the sea side of the automated terminal and the turnover process of the container inside the terminal is accelerated. This paper considers the joint scheduling problem of the quay crane and the Automated Guided Vehicle（AGV） with the grouping work surface under the interference constraint. With the goal of minimum weighted sum of the quay crane, AGV completion time and AGV waiting time, considering the interference constraints of the quay crane and AGV congestion waiting in the actual operation, the joint scheduling optimization model of the quay crane and AGV is established. For the scheduling scheme of the two devices, this paper proposes the dynamic scheduling for quay cranes and grouping work surface scheduling mode for AGVs. The examples of different scales are designed and solved by Genetic Algorithm（GA）. The calculation results are compared with the traditional scheduling mode. The results show that this algorithm can effectively improve the efficiency of quay cranes and AGVs operation, reduce the waiting time and number of jams of AGV, it provides the basis for the actual operation of the terminal.

Key words: automated terminal, joint scheduling, interference constraint, grouping work surface, genetic algorithm

摘要：

为解决自动化码头海侧多阶段设备作业的协调问题，加快集装箱在码头内部的周转过程。考虑干扰约束下分组作业面的的岸桥自动导引小车（AGV）联合调度问题。以岸桥、AGV完工时间和AGV等待时间加权总和最小为目标，考虑岸桥实际操作中的干扰约束与AGV堵塞等待等情况，建立岸桥与AGV联合调度优化模型。提出岸桥动态调度与AGV分组作业面调度模式，设计不同规模的算例，并采用遗传算法（GA）进行求解，将计算结果与传统调度模式进行对比。结果表明，该算法能有效提高岸桥与AGV作业效率，降低AGV的等待时间与堵塞次数，为码头实际作业提供依据。

关键词: 自动化码头, 联合调度, 干扰约束, 分组作业面, 遗传算法