A comparison between ACO algorithms for the set covering problem

被引：0
|
作者：
Lessing, L [1 ]
Dumitrescu, I [1 ]
Stützle, T [1 ]
机构：
[1] Tech Univ Darmstadt, Intelligent Grp, Darmstadt, Germany
来源：
ANT COLONY OPTIMIZATION AND SWARM INTELLIGENCE, PROCEEDINGS | 2004年 / 3172卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we present a study of several Ant Colony Optimization (ACO) algorithms for the Set Covering Problem. In our computational study we emphasize the influence of different ways of defining the heuristic information on the performance of the ACO algorithms. Finally, we show that the best performing ACO algorithms we implemented, when combined with a fine-tuned local search procedure, reach excellent performance on a set of well known benchmark instances.
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页码：1 / 12
页数：12
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