Abstract: To improve the efficiency of collaborative operation between twin single-side cantilever yard cranes and Automated Guided Vehicle (AGV),a two-stage optimization model was constructed for the twin single-side cantilever yard cranes scheduling and AGV path planning problems.The first-stage model was established with the minimum maximum completion time,and the parking position of AGV and twin single-side cantilever yard cranes scheduling problem were optimized.An improved Genetic Simulated Annealing Algorithm was designed to solve the model.In the second-stage model,according to the obtained parking position and time information,an improved Dijkstra′s algorithm was used to solve the initial path without considering AGV conflicts,and then a hybrid conflict resolution strategy was adopted to solve the AGV conflict problem.The Shanghai Yangshan Phase IV Automated Terminal was used as background to design the instances,and CPLEX was used to verify the accuracy of the model.The effectiveness of the algorithm was verified by comparison with other algorithms.The results showed that the established model and proposed strategy could effectively improve the efficiency of single-side cantilever yard cranes and AGV.

Key words: single-side cantilever yard cranes, yard crane scheduling, path planning, heuristic algorithms

摘要： 为提高单悬臂场桥与自动导引车(AGV)协同作业效率,针对双单悬臂场桥调度和AGV路径规划问题,构建两阶段优化模型。第一阶段以最大完工时间最少为优化目标建立模型,优化AGV停车位和双单悬臂场桥调度,设计遗传模拟退火算法求解;第二阶段根据第一阶段得到的AGV停车位置及时间信息,首先在不考虑AGV冲突的情况下采用改进的Dijkstra算法求解AGV初始路径,然后采用混合冲突解决策略解决箱区内AGV冲突问题。以上海洋山四期自动化码头为背景设计算例,用CPLEX验证模型准确性,通过与其他算法的比较验证了算法的有效性。结果表明,所建模型和提出的策略能有效提高单悬臂场桥和AGV的工作效率。

关键词: 单悬臂场桥, 场桥调度, 路径规划, 启发式算法