摘要
基于TSP问题,提出了一种基于粒子群-蚁群算法相互融合的综合优化算法对移动机器人路径规划问题进行研究.通过粒子群算法对全局路径实施粗略搜索,获得部分次优解,在获得次优解的路径上进行信息素分布,再采用蚁群算法进行精确搜索,得到路径规划的最优解.实验结果表明:粒子群-蚁群融合优化算法在路径寻优上优于蚁群算法及粒子群算法.
Aiming at the TSP problem,in order to research the optimal path planning for mobile robot,a new algo-rithm based on ant colony algorithm combined with particle swarm algorithm（ PAAAA）has been proposed. Firstly, using the particle swarm optimization to search the global path,the second best solution is obtained. Then,after dis-tributing the pheromones on the second best solution paths,using ant colony algorithm to finish accurate searching. Last,the optimal solution of path planning is achieved. The simulation result shows that PAAA is better than single ant colony algorithm or single particle swarm optimization.
出处
《江西师范大学学报（自然科学版）》
CAS
北大核心
2014年第3期274-277,共4页
Journal of Jiangxi Normal University(Natural Science Edition)
基金
江苏省自然科学基金(BK20131205)资助项目
关键词
蚁群算法
粒子群算法
TSP问题
路径规划
移动机器人
ant colony algorithm
particle swarm optimization
TSP problem
path planning
mobile robot
