计算机工程2012，Vol.38Issue(23)：190-193,197,5.DOI:10.3969/j.issn.1000-3428.2012.23.047
求解子旅行商问题的改进蚁群算法
Improved Ant Colony Algorithm for Solving Subset Traveling Salesman Problem
摘要
Abstract
Existing ant colony algorithm is easy precocious and easy to fall into local optimum when the Subset Traveling Salesman Problem (STSP) is solved through it. In order to solve this problem, the crowding factor is embedding into the state transition and the pheromone update according to the characteristic of the STSP. It makes its global searching ability enhance remarkably. An efficient neighborhood searching technique and a simple and effective local mutation technique are introduced into this algorithm to improve further the quality of solution. Experimental results show that the improved algorithm has much higher quality and stability than that of existing ant colony algorithm.关键词
旅行商问题/局部最优/拥挤因子/邻域搜索/局部变异/蚁群算法Key words
Traveling Salesman Problem(TSP)/ local optimum/ crowding factor/ neighborhood searching/ local mutation/ ant colony algorithm分类
信息技术与安全科学引用本文复制引用
牟廉明..求解子旅行商问题的改进蚁群算法[J].计算机工程,2012,38(23):190-193,197,5.基金项目
国家自然科学基金资助项目(10872085) （10872085）
四川省科技厅应用基础研究基金资助项目(07JY029-125) （07JY029-125）
四川省教育厅重大培育基金资助项目(07ZZ016) （07ZZ016）
