Optimization based on Multi-type Ants for the Traveling Salesman Problem

被引：0
|
作者：
Costa Salas, Y. J. [1 ]
Castano Perez, N. J. [2 ]
Betancur, J. F. [1 ]
机构：
[1] Univ Manizales, Dept Econ, Manizales, Colombia
[2] Univ Manizales, Dept Engn, Manizales, Colombia
来源：
2014 9TH COMPUTING COLOMBIAN CONFERENCE (9CCC) | 2014年
关键词：
optimization; bioinspired computation; ant algorithms; multi-type ants; traveling salesman; COLONY OPTIMIZATION; ROUTING PROBLEM; TIME; ALGORITHM;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper proposes an algorithm based on multi-type ants (so-called Multi-type Ant Colony System, MACS) for solving the Traveling Salesman Problem (TSP). Multiple ant types cooperate (through pheromone exchange) and compete (by mean of repulsion mechanism) among them in order to increase the efficacy in the search process. The obtained experimental results has been compared against benchmark results from OR literature. In particular for large scale TSP, the algorithmic proposal M-ACS shows competitive results regarding to the efficacy.
引用
收藏
页码：144 / 149
页数：6
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