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基于遗传变异蚁群算法的机器人路径规划的改进
引用本文:李学洋,李悦,张亚伟. 基于遗传变异蚁群算法的机器人路径规划的改进[J]. 电子设计工程, 2012, 20(15): 38-40,43
作者姓名:李学洋  李悦  张亚伟
作者单位:辽宁石油化工大学信息与控制工程学院,辽宁抚顺,113001
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。

关 键 词:变异因子  遗传算法  蚁群算法  路径规划

Improved ant colony algorithm based on genetic variation apply in robots path planning
LI Xue-yang,LI Yue,ZHANG Ya-wei. Improved ant colony algorithm based on genetic variation apply in robots path planning[J]. Electronic Design Engineering, 2012, 20(15): 38-40,43
Authors:LI Xue-yang  LI Yue  ZHANG Ya-wei
Affiliation:(School of Information and Control Engineering,Liaoning Shihua University,Fushun 113001,China)
Abstract: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.
Keywords:mutagenic factors  genetic algorithms  ant colony algorithm  path planning
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