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基于自适应路径选择和信息素更新的蚁群算法
引用本文:赵宝江,李士勇,金俊.基于自适应路径选择和信息素更新的蚁群算法[J].计算机工程与应用,2007,43(3):12-15.
作者姓名:赵宝江  李士勇  金俊
作者单位:哈尔滨工业大学,控制科学与工程系,哈尔滨,150001;牡丹江师范学院,数学系,黑龙江,牡丹江,157012;哈尔滨工业大学,控制科学与工程系,哈尔滨,150001;牡丹江师范学院,数学系,黑龙江,牡丹江,157012
摘    要:针对蚁群算法加速收敛和早熟、停滞现象的矛盾,提出了一种基于自适应路径选择和信息素更新的蚁群算法,以求在加速收敛和防止早熟、停滞现象之间取得很好的平衡。该算法根据优化过程中解的分布状况,自适应地调整路径选择策略和信息量更新策略。基于旅行商问题的实验验证了算法比一般蚁群算法具有更好的全局搜索能力、收敛速度和解的多样性。

关 键 词:蚁群算法  信息素  分散度  旅行商问题
文章编号:1002-8331(2007)03-0012-04
修稿时间:2006-11

Ant colony algorithm based on adaptive selection of paths and pheromone updating
ZHAO Bao-jiang,LI Shi-yong,JIN Jun.Ant colony algorithm based on adaptive selection of paths and pheromone updating[J].Computer Engineering and Applications,2007,43(3):12-15.
Authors:ZHAO Bao-jiang  LI Shi-yong  JIN Jun
Affiliation:1.Department of Control Science and Engineering,Harbin Institute of Technology,Harbin 150001,China ;2.Department of Mathematics,Mudanjing Teachers College,Mudanjing,Heilongjiang 157012,China
Abstract:To settle the contradictory between convergence speed and precocity and stagnation in ant colony algorithm,an ant colony algorithm,which is based on adaptive selection of the paths and dynamic updating of pheromone,is presented.By dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating according to the distribution of the solutions ,the algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. Experimental results on traveling salesman problem show that the method presented in this paper has a better global searching ability,higher convergence speed and solution diversity than that of classical ant colony algorithm.
Keywords:ant colony algorithm  pheromone  dispersed degree  traveling salesman problem
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