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DOI:
Journal of Software:2004.15(2):185-192

基于变异和动态信息素更新的蚁群优化算法
朱庆保,杨志军
(南京师范大学,计算机科学系,江苏,南京,210097;爱丁堡大学,电子工程系,EH9 3JL,英国)
An Ant Colony Optimization Algorithm Based on Mutation and Dynamic Pheromone Updating
ZHU Qing-Bao,YANG Zhi-Jun
()
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Received:December 19, 2002    Revised:June 20, 2003
> 中文摘要: 尽管蚁群优化算法在优化计算中已得到了很多应用,但在进行大规模优化时,其收敛时间过长仍是应用该算法的一个瓶颈.为此,提出了一种高速收敛算法.该算法采用一种新颖的动态信息素更新策略,以保证在每次搜索中,每只蚂蚁都对搜索做出贡献;同时,还采取了一种独特的变异策略,以对每次搜索的结果进行优化.计算机实验结果表明,该算法与最新的改进蚁群优化算法相比,其收敛速度提高了数十倍乃至数百倍以上.
Abstract:Despite the numerous applications of ACO (ant colony optimization) algorithm in optimization computation, it remains a computational bottleneck that the ACO algorithm costs too much time in order to find an optimal solution for large-scaled optimization problems. Therefore, a quickly convergent version of the ACO algorithm is presented. A novel strategy based on the dynamic pheromone updating is adopted to ensure that every ant contributes to the search during each search step. Meanwhile, a unique mutation scheme is employed to optimize the search results of each step. The computer experiments demonstrate that the proposed algorithm makes the speed of convergence hundreds of times faster than the latest improved ACO algorithm.
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基金项目:ant colony optimization;nearest neighbour;dynamic pheromone updating;mutation algorithm ant colony optimization;nearest neighbour;dynamic pheromone updating;mutation algorithm
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朱庆保,杨志军.基于变异和动态信息素更新的蚁群优化算法.软件学报,2004,15(2):185-192

ZHU Qing-Bao,YANG Zhi-Jun.An Ant Colony Optimization Algorithm Based on Mutation and Dynamic Pheromone Updating.Journal of Software,2004,15(2):185-192