集装箱码头上多自动引导车的调度和路径规划  

Scheduling and path planning of multiple automatic guided vehicles in container terminals

作　　者：李静 朱小林[1,2] LI Jing;ZHU Xiaolin(College of Arts and Sciences, Shanghai Maritime University, Shanghai 201306, China;Institute of Logistics and Engineering, Shanghai Maritime University, Shanghai 201306, China)

机构地区：[1]上海海事大学文理学院,上海201306 [2]上海海事大学物流科学与工程研究院,上海201306

出　　处：《计算机集成制造系统》2022年第5期1449-1461,共13页Computer Integrated Manufacturing Systems

基　　金：国家社会科学基金重大资助项目(18ZDA052);上海市科委科研计划资助项目(17DZ2280200)。

摘　　要：针对自动化集装箱码头上多自动引导车(AGV)的调度和路径规划问题,在考虑AGV负载以及冲突的情况下,建立了以最小化AGV能量消耗为目标的数学模型。设计了两个阶段的算法对模型进行求解,第一阶段基于任务组合分解,利用灰狼优化算法在最短路径下优化AGV调度,第二阶段对于较优的AGV调度,进一步利用基于Floyd的时间冲突预测算法对其路径进行优化,以达到预防冲突的结果。通过实验验证了不同问题规模下算法的可行性和有效性,结果表明所设计算法能有效减少编码长度,得到的结果质量、运行时间和收敛情况都优于其他算法所得,该算法能够有效地解决不同规模下多AGV的调度和预防冲突的路径规划问题,减少AGV的能量消耗。Aiming at the scheduling and path planning of multiple Automated Guided Vechicles(AGVs)on automated container terminals,a mathematical model with the goal of minimizing AGV energy consumption was established by considering AGV load and conflicts.Two stages algorithm was designed to solve this model.In the first stage,Grey Wolf Optimizer(GWO)was used to optimize AGV scheduling under the shortest path based on task combination decomposition.In the second stage,for the better AGV scheduling,Floyd based time conflict prediction algorithm was further used to optimize its path to achieve the result of conflict prevention.Experiments verified the feasibility and effectiveness of the designed algorithm under different problem scales.The results showed that the proposed algorithm could effectively reduce the code length,and the result quality,running time and convergence were better than those obtained by other algorithms.It could effectively solve the scheduling of multiple AGVs under different scales and prevent conflict path planning,and reduce the energy consumption of AGVs.

关 键 词：自动化集装箱码头 多自动引导小车调度 灰狼优化算法 路径规划 弗洛伊德算法 预防冲突 

分 类 号：U691.3[交通运输工程—港口、海岸及近海工程] TP18[交通运输工程—船舶与海洋工程]