【作者】 林天建； 余春艳；

【Author】 Lin Tian-fian Yu Chun-yan (College of Mathematics and computer science,Fuzhou University,Fuzhou,Fujian,350002)

【机构】 福州大学数学与计算机科学学院；

【摘要】 尽管蚁群算法在很多领域的应用表现出了很好的性能,但是其收敛速度慢仍是它的一个瓶颈．为了解决这种问题, 文章提出了一种新的高速收敛蚁群算法。该算法在 MMAS 基础上,结合粒子群算法中粒子位置转移的机制,采用一种新颖的最近邻居选择策略、并进行动态信息素更新策略,以保证在每次搜索中,都能迅速向较优解靠拢．同时,还采取了一种局部变异策略,以对每次搜索的结果进行优化．更多还原

【Abstract】 Despite the numerous applications of ACO(Ant Colony Optimization)algorithm in optimization field and show the good performance,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.On the basis of the max-min ant system,a mechanism in transformation of location of particle swarm optimization and closet neighbor strategy along with the dynamic pheromone updating are adopted to ensure that each ant could quickly access to the nice route.Meanwhile,a local mutation mechanism is employed to optimize the search results of each circulation.更多还原