Abstract:

In the path planning of the multi-AGV（Automated Guided Vehicles） system, the topology map model of the AGV is constructed, and the tabu algorithm based on the global neighborhood search is designed to solve the shortest path combinatorial optimization problem efficiently and accurately. Then group experiments under different scale calculation examples are conducted to verify the optimization effect of the tabu search algorithm on path energy consumption attributes, time attributes, and path load balancing target parameters, in order to improve the stability and efficiency of the multi-AGV system.

Key words: Automatic Guided Vehicle（AGV）, path planning, tabu search algorithm, combinatorial optimization

摘要：

在多自动导引车（Automated Guided Vehicles，AGV）系统的路径规划中，构建AGV的拓扑结构地图模型，设计基于全局邻域搜索的禁忌算法，以高效准确地解决最短路径的组合优化问题，并进行不同规模算例下的分组实验，验证禁忌搜索算法对路径能耗属性、时间属性和路径负载均衡目标参数的优化效果，来提高多AGV系统的稳定性和高效性。

关键词: 自动导引车（AGV）, 路径规划, 禁忌搜索算法, 组合优化