A new minimum pheromone threshold strategy (MPTS) for max-min ant system

被引：22
|
作者：
Wong, Kuan Yew [1 ]
See, Phen Chiak [1 ]
机构：
[1] Univ Teknol Malaysia, Fac Mech Engn, Dept Ind & Mfg Engn, Skudai 81310, Malaysia
来源：
APPLIED SOFT COMPUTING | 2009年 / 9卷 / 03期
关键词：
Metaheuristics; Combinatorial optimization; Ant colony optimization (ACO); Max-min ant system (MMAS); QUADRATIC ASSIGNMENT PROBLEM; COLONY OPTIMIZATION; ALGORITHMS; SWARM;
D O I：
10.1016/j.asoc.2008.11.011
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In recent years, various metaheuristic approaches have been created to solve quadratic assignment problems (QAPs). Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. Although it has solved some QAPs successfully, it still contains some weaknesses and is unable to solve large QAP instances effectively. Thereafter, various suggestions have been made to improve the performance of the ACO algorithm. One of them is through the development of the max-min ant system (MMAS) algorithm. In this paper, a discussion will be given on the working structure of MMAS and its associated weaknesses or limitations. A new strategy that could further improve the search performance of MMAS will then be presented. Finally, the results of an experimental evaluation conducted to evaluate the usefulness of this new strategy will be described. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码：882 / 888
页数：7
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