初始信息素不均匀分布的蚁群算法

The Ant Colony Algorithm for Uneven Distribution of Initial Pheromones

蚁群算法初始信息素的等值分布导致其在移动机器人路径规划中存在收敛性差、收敛速度慢等不足,为此,文章提出一种初始信息素不均匀分布策略的蚁群算法。初始信息素不均匀分布策略的核心思想是基于双向搜索,根据起点与终点附近首个障碍物信息构建初始信息素增强区域,以此降低算法初期搜索的盲目性,进而提升算法收敛性能。仿真实验结果表明,该改进蚁群算法搜索成功率高、收敛速度快,可提升前期搜索路径质量。

The equivalent distribution of initial pheromones in ant colony algorithm leads to its poor convergence and slow convergence speed in mobile robot path planning.Therefore,an improved ant colony algorithm based on uneven distribution of initial pheromones is proposed.The core idea of the initial pheromone uneven distribution strategy is based on two-way search,and according to the information of the first obstacle near the starting point and the end point,the initial pheromone enhancement region is constructed,so as to reduce the blindness of initial retrieval and improve the convergence performance of the algorithm.The simulation results show that the improved ant colony algorithm based on the initial pheromone uneven distribution strategy has high search success rate,fast convergence speed,and can improve the quality of early search path.