自动化码头AGV调度与路径规划双层优化模型

A Two-layer Optimization Model for Automated Terminal AGV Scheduling and Route Planning

自动化集装箱码头设备的合理调度是提升码头运作效率的关键。为实现合理调度,针对自动化集装箱码头自动导引车(automated guided vehicle,AGV)的任务调度和路径规划问题,考虑其在行驶过程中的冲突、拥堵以及充电问题,设定冲突解决策略和充电策略,建立双层模型并设计混合遗传算法与Dijkstra算法结合的算法进行求解。结果表明,混合遗传算法相较于一般遗传算法求解质量更高,建立的双层模型能合理决策自动导引车任务安排和路径规划问题,所设计的算法能有效解决和避免自动导引车之间的冲突与拥堵,充电策略能合理安排充电序列、降低排队等待时间、提升码头运作效率。

The rational scheduling of resources and equipment in an automated container terminal is the key to improve the operation efficiency of the terminal.In order to realize reasonable scheduling and path planning of automated guided vehicle(AGV)on an automated container terminal,the conflict resolution strategy and charging strategies were set up on the basis of considering the conflict,congestion and charging problems of AGV.A two-layer model was established.An algorithm combining hybrid genetic algorithm and Dijkstra algorithm was designed to solve the problem.The results show that the hybrid genetic algorithm has higher solving quality,and the established twolayer model can make reasonable decisions on the task arrangement and path planning of the automatic guided vehicles.The designed algorithm can effectively solve conflicts between automatic guided vehicles and avoid congestion.The charging strategy can reasonably arrange charging sequence and reduce queuing time,which can improve the operation efficiency of the automated terminal.