求解旅行商问题的模拟退火蚁群算法  

Hybrid algorithm combining ant colony optimization algorithm with simulated annealing algorithm optimization

作　　者：江新姿[1] 高尚[1] 陈建忠[2] 

机构地区：[1]江苏科技大学电子信息学院,江苏镇江212003 [2]解放军理工大学气象学院,江苏南京211101

出　　处：《计算机工程与设计》2008年第6期1491-1493,共3页Computer Engineering and Design

基　　金：江苏省“青蓝工程”基金项目(苏教师〔2007〕2号);江苏省计算机信息处理技术重点实验室开放课题基金项目(KJS0601)

摘　　要：根据蚁群算法与模拟退火算法的特性,提出了求解旅行商问题的混合算法。由模拟退火算法生成信息素分布,然后由蚁群算法根据累计更新的信息素找出若干组解,再经过模拟退火算法在邻域内找另外一个解的操作,得到更有效的解。与模拟退火算法、标准遗传算法、蚁群算法和随机初始化的蚁群算法进行比较,4种混合算法效果都比较好,策略D的混合算法效果最好。By use of the properties of ant colony algorithm and simulated annealing algorithm,a hybrid algorithm is proposed to solve the traveling salesman problems.First,it adopts simulated annealing algorithm to give information pheromone to distribute.Second,it makes use of the ant colony algorithm to get several solutions through information pheromone accumulation and renewal.Finally,by searching a solution of neighborhood of simulated annealing algorithm,the effective solutions are obtained.Comparing with the simulated annealing algorithm,the standard genetic algorithm,the standard ant colony algorithm,and statistics initial ant colony algorithm,all the 4 hybrid algorithms are proved effective.Especially the hybrid algorithm with strategy D is a simple and effective better algorithm than others.

关 键 词：蚁群算法 模拟退火算法 旅行商问题 遗传算法 混合算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]