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基于混合信息素递减的蚁群算法
引用本文:姜长元.基于混合信息素递减的蚁群算法[J].计算机工程与应用,2007,43(32):62-64.
作者姓名:姜长元
作者单位:湖州师范学院 理学院,浙江 湖州 313000
摘    要:根据蚁群算法信息素更新的特性,提出了求解旅行商问题的混合信息素递减的蚁群算法。把基本蚁群的三种不同的信息素更新方式混合在一起,同时提出了信息素递减更新的方法。新的更新方式避免了蚂蚁在寻找最优解的过程中,由于禁忌表元素的逐渐增加而限制蚂蚁巡游路径选择的缺点,减少了巡游后期信息素对于后继蚂蚁的影响,提高了后继蚂蚁的巡游质量。仿真实验表明了该混合算法的有效性。

关 键 词:蚁群算法  信息素  旅行商问题
文章编号:1002-8331(2007)32-0062-03
修稿时间:2007-01

Ant colony algorithm based on multiplicate pheromone declining
JIANG Chang-yuan.Ant colony algorithm based on multiplicate pheromone declining[J].Computer Engineering and Applications,2007,43(32):62-64.
Authors:JIANG Chang-yuan
Affiliation:Faculty of Science,Huzhou Teachers College,Huzhou,Zhejiang 313000,China
Abstract:By use of the properties of pheromone of ant colony algorithm,an ant colony algorithm based on multiplicate pheromone declining is proposed to solve the Traveling Salesman Problems(TSP).Three modes of updating the pheromone are hybridized.A new methods descending updating pheromone is introduced.The new algorithm avoids the defect that the gradually increased tabu table restricts the selection of ant cruising route during ants looking for the optimized solution,and it reduces the influence of pheromone on subsequent ants,enhances the subsequent ants’ cruising quality.The simulation results on TSP show the validity of this algorithm.
Keywords:ant colony algorithm  pheromone  Traveling Salesman Problems(TSP)
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