摘要
蚁群算法在解决旅行商等著名问题时得到了卓有成效的应用,但解决大规模问题时,其收敛速度较慢且耗时较长;同样,郭涛算法在解决复杂优化问题时取得了良好效果,但会产生大量无为的冗余迭代,求解效率低;文章汲取蚁群算法和郭涛算法的优点,提出混合蚁群算法,建立混合蚁群算法数学模型,得到时间效率和求解效率都比较好的一种新的启发式算法。
The ant colony arithmetic has been successfully applied to solving the famous traveling salesman problem, but when it confronts large-scale problems, its convergence velocity becomes relatively slow and its computation is time-consuming. Similarly, Guo＇s algorithm has produced good results when the complex optimization problems are solved, but a great number of useless redundancy iterations come out and the solution efficiency is low. This paper makes use of merits of both the ant colony arithmetic and Guo＇s algorithm to propose a mixed ant colony arithmetic, and a mixed ant colony arithmetic mathematical model is established. The algorithm is a new enlightening method, and its time efficiency and solution efficiency are much better.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2009年第5期684-688,共5页
Journal of Hefei University of Technology：Natural Science
基金
安徽省教育厅自然科学基金资助项目(2005KJ079)
安徽省2007教研资助项目(JYXM372)
关键词
蚁群算法
旅行商问题
郭涛算法
混合蚁群算法
物流配送
ant colony algorithm traveling salesman problem
Guo＇s algorithm
mixed ant colony algorithm logistics distribution
