摘要
为了在现有的路径规划中找到一条最优路径,针对该领域提出一种改进的蚁群算法。该算法在简单蚁群算法的基础上,引入狼群分配理论更新信息素浓度,加快计算初期的算法收敛。通过对环境信息素浓度时刻监控,当出现信息素聚集则改变蚂蚁的行动路径,避免算法陷入停滞。引入模糊函数对所得路径进行综合评价,将系统消耗加入评价体系,通过模糊评价得出符合实际需要的最佳路径。实验结果验证了其在实际应用中的可行性和有效性。
In order to find an optimal path in the existing path planning, an improved ant colony algorithm is proposed in this paper. The algorithm is based on simple ant colony algorithm, introducing the theory of distribution update pheromone concentration of wolves, accelerate the convergence of the algorithm. Through the calculation of the initial pheromone concentration on the environment monitor, when the aggregation pheromone change action of ant algorithm, avoid stagnation the introduction of fuzzy comprehensive evaluation. The function of the path, the system consumption into evaluation system, the optimal path was obtained by the fuzzy evaluation to meet the actual needs. The experimental results show its feasibility and effectiveness in practical application.
作者
裴晓芳
张杨
丁立
Pei Xiaofang;Zhang Yang;Ding Li(Jiangsu Key Laboratory of Meteorological Observation and Information Processing,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science and Technology,Nanjing 210044,China;Binjiang College,Nanjing University of Information Science g.-Technology,Nanjing 210044,China;College of Electronic and Information Engineering,Nanjing University of Information Science ~,-Technology,Nanjing 210044,China)
出处
《电子测量技术》
2018年第16期28-32,共5页
Electronic Measurement Technology
基金
江苏省气象探测与信息处理重点实验室开放课题(KDXS1401)
江苏高校品牌专业建设工程资助项目
江苏省“信息与通信工程”优势学科建设项目资助
关键词
智能导航
蚁群算法
狼群分配理论
模糊控制
intelligent navigation
ant colony algorithm
wolves distribution theory
fuzzy control
