基于改进自适应PSO与GA的车辆检查点路径规划设计  

.Design of Vehicle Checkpoint Path Planning Based on Improved Adaptive PSO and GA

作　　者：田津休 董航 TIAN Jinxiu;DONG Hang(School of Mechanical Engineering,Yangzhou University,Jiangsu 225127,China)

机构地区：[1]扬州大学机械工程学院,江苏225127

出　　处：《电子技术（上海）》2023年第11期6-8,共3页Electronic Technology

摘　　要：阐述改进自适应的粒子群算法与遗传算法的设计和比较。此设计案例将所给重要位置设为AGV小车的车辆检查点,除了第一次通过时需要检测平面度等公差,往后不定期次对相关环境进行主要监测,考虑资源的节省问题,每次通过所有位置后总路程应最短。基于两种优化算法在此问题中的多次对比,最终选择实际路程更优的改进自适应遗传算法方案。This paper describes the design and comparison of improved adaptive particle swarm optimization algorithm and genetic algorithm.This design case will set the given important position as the vehicle inspection point for the AGV car.In addition to the need to check for flatness and other tolerances during the first pass,the relevant environment will be monitored periodically in the future to consider resource conservation.The total distance after passing through all positions should be the shortest.Based on multiple comparisons between two optimization algorithms in this problem,the improved adaptive genetic algorithm scheme with better actual distance was ultimately chosen.

关 键 词：改进自适应 粒子群算法 遗传算法 车辆检查 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP274[自动化与计算机技术—控制科学与工程]