计算机技术与发展2016，Vol.26Issue(12)：1-5,5.DOI:10.3969/j.issn.1673-629X.2016.12.001
自适应蚁群算法求解最短路径和TSP问题
Solving of Shortest Path Problem and TSP with Adaptive Ant Colony Algorithm
摘要
Abstract
Direction guiding is utilized in the initial pheromone avoiding ant colony in the initial stage to blindly random search and to waste more time. Moreover,a dynamic factor ( hyperbolic tangent function) is invited in the global renewal process to update adaptively the pheromone concentration on the optimal path,in which way the possibility of obtaining the global optimal solution is increased. Then two examples are optimized with the improved algorithm,and the optimization results are in step with the actual,illustrating the effective-ness and practicability of the improved algorithm.关键词
蚁群算法/最短路径/方向引导/动态因子/旅行商问题Key words
ant colony algorithm/shortest path/direction guiding/dynamic factor/TSP分类
信息技术与安全科学引用本文复制引用
易正俊,李勇霞,易校石..自适应蚁群算法求解最短路径和TSP问题[J].计算机技术与发展,2016,26(12):1-5,5.基金项目
国家自然科学基金资助项目(69674012) （69674012）
重庆市科技攻关计划(CSTC2009AC3037) （CSTC2009AC3037）
