基于改进人工鱼群算法的最短路径问题研究  

Research on shortest path problem based on improved artificial fish swarm algorithm

作　　者：檀洪森 TAN Hongsen(Nanning College for Vocational Technology,Nanning 530008,China)

机构地区：[1]南宁职业技术学院,南宁530008

出　　处：《计算机应用文摘》2024年第12期94-98,共5页Chinese Journal of Computer Application

摘　　要：为提高智能机器人的路径寻优能力,文章提出一种基于检测算子和经验学习的鱼群算法(Detection Operator and Experiecnce Learning Artificial Fish Swarm Algorithm,DOEL-AFSA)。仿真实验结果表明,DOEL-AFSA得到的最短路径比鱼群算法(AFSA)、动态分级蚁群算法(WAS)等算法更好,其求解效率更高。To improve the path optimization ability of intelligent robots,this article proposes a Detection Operator and Experience Learning Artificial Fish Swarm Algorithm(DOEL-AFSA)based on detection operators and experience learning.Simulation results show that the shortest path obtained by DOEL-AFSA is better than that obtained by algorithms such as AFSA and WAS,and its solving efficiency is higher.

关 键 词：最短路径规划 鱼群算法 经验学习算法 检测算子 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]