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基于禁忌搜索的多AGV系统路径优化算法
引用本文:陈展,公建宁,刘媛媛,徐京邦.基于禁忌搜索的多AGV系统路径优化算法[J].计算机工程与应用,2021,57(10):273-278.
作者姓名:陈展  公建宁  刘媛媛  徐京邦
作者单位:机械科学研究总院 机科发展科技股份有限公司,北京 100044
基金项目:工信部新一代人工智能产业创新重点任务
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  

Multi-AGV System Path Optimization Algorithm Based on Tabu Search
CHEN Zhan,GONG Jianning,LIU Yuanyuan,XU Jingbang.Multi-AGV System Path Optimization Algorithm Based on Tabu Search[J].Computer Engineering and Applications,2021,57(10):273-278.
Authors:CHEN Zhan  GONG Jianning  LIU Yuanyuan  XU Jingbang
Affiliation:Machine Development Technology Co., Ltd., China Academy of Machinery Science and Technology, Beijing 100044, China
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.
Keywords:Automatic Guided Vehicle(AGV)  path planning  tabu search algorithm  combinatorial optimization  
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