On Multi-Behavior Based Multi-Colony Ant Algorithm for TSP

被引：1
|
作者：
Liu, Sheng [1 ]
You, Xiaoming [2 ]
机构：
[1] Shanghai Univ Engn Sci, Sch Management, Shanghai, Peoples R China
[2] Shanghai Univ Engn Sci, Coll Elect & Elect Engn, Shanghai, Peoples R China
来源：
2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 3, PROCEEDINGS | 2009年
基金：
上海市自然科学基金;
关键词：
Ant Colony System(ACS); hybrid behavior; immigrant operator; Traveling Salesman Problem (TSP);
D O I：
10.1109/IITA.2009.464
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level respectively according to immigrant operator. This parallel and cooperating optimization scheme by using different behavioral characteristics and inter-colonies migration strategies can help the algorithm skip from local optimum effectively. The experimental results for TSP show the validity of this algorithm.
引用
收藏
页码：348 / +
页数：2
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