摘要
针对基本蚁群算法在机器人路径规划问题中容易陷入局部最优的问题,提出了一种改进的蚁群算法,利用遗传算法加入了变异因子使最优路径产生变异,从而降低了蚁群算法陷入局部极小的可能性,同时改善了基本蚁群算法不收敛或收敛速度比较慢的缺点,加快了收敛速度,增加了最优解的多样性。
Aiming at solving the problem of falling into local optimum of the basic ant colony algorithm in robot path planning, this paper introduced a modified ant colony clustering algorithm. Combined with genetic algorithm, the modified algorithm was added with mutagenic factors. The mutagenic factors, which made the best path mutated, broadened the diversity of high- quality solutions and speeded up the convergence.
出处
《电子设计工程》
2012年第15期38-40,43,共4页
Electronic Design Engineering
关键词
变异因子
遗传算法
蚁群算法
路径规划
mutagenic factors
genetic algorithms
ant colony algorithm
path planning
