计算机工程与应用Issue(24)：24-27,4.DOI:10.3778/j.issn.1002-8331.1306-0238
基于变异和启发式选择的蚁群优化算法
Ant colony algorithm based on mutation features and selected heuristic
摘要
Abstract
There are some shortcomings in the traditional ant colony algorithm as the algorithm costs too much time to get an optimal solution and easily falls into a stagnation behavior. To solve these problems, this paper puts forward a new ant colony algorithm based on mutation features and selected heuristic. The new algorithm uses the basic characteristics between the adja-cent nodes in the optimal path, avoiding the large scope searching. It can get better initial solutions and greatly reduces the time complexity of the algorithm. It also uses the selected heuristic to accelerate the convergence process. With the 2-exchanged method, the mutation strategy not only enhances the mutation efficiency, but also improves the mutation quality. Combined with classic TSP instances, the MFSHACO algorithm shows good performance.关键词
蚁群算法/旅行商问题(TSP)/变异/启发式选择Key words
ants colony system/Traveling Salesman Problem(TSP)/mutation/selected heuristic分类
信息技术与安全科学引用本文复制引用
方霞,席金菊..基于变异和启发式选择的蚁群优化算法[J].计算机工程与应用,2013,(24):24-27,4.基金项目
湖南省教育厅项目（No.09C704）。 （）
