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基于蚁群优化算法的障碍距离分析 被引量:1

Obstacles distance using ant colony optimization
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摘要 传统的距离计算往往因不考虑实际情况中障碍物的问题而不实用,借鉴了机器人路径规划问题的解决思路,将遗传算法中交叉算子引入到蚁群优化算法的路径寻优过程中,提出一种进化蚁群优化算法的障碍距离算法,能够很好的降低搜索陷入局部最优的可能性。实验结果表明,该方法不仅能处理任何复杂形状的障碍,与基于遗传算法的障碍距离计算方法相比,具有较好的路径寻优能力。 Traditional distance calculation is not used well without considering the actual question of obstacles. On the basis ofthe paper used in robot path planning problem solving ideas, and the crossover operation of genetic algorithm is used in the ant colony system for path optimization. A novel algorithm of obstacle distance using ant colony optimization is proposed, and the probability of local optimum is reduced. Experimental results show that the proposed algorithm is capable of handling any complex shape obstacles and has better path planning optimization ability than genetic algorithm.
出处 《计算机工程与设计》 CSCD 北大核心 2009年第2期429-432,共4页 Computer Engineering and Design
基金 2008河南省高校科技创新人才支持计划基金项目(2008HASTIT012) 辽宁工程技术大学地理空间信息技术与应用实验室开放基金项目(2005003) 河南工业大学博士基金项目(2008BS003) “空间数据挖掘与信息共享教育部重点实验室(福州大学)”开放基金项目(200807)
关键词 空间分析 障碍距离 蚁群优化算法 遗传算法 交叉算子 spatial analysis obstacles distance ant colony optimization genetic algorithm crossover operator
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