MAX-MIN Ant System and local search for the traveling salesman problem

被引:410
作者
Stutzle, T
Hoos, H
机构
来源
PROCEEDINGS OF 1997 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION (ICEC '97) | 1997年
关键词
D O I
10.1109/ICEC.1997.592327
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Ant System is a general purpose algorithm inspired by the study of the behavior of Ant Colonies. It is based on a cooperative search paradigm that is applicable to the solution of combinatorial optimization problems. In this paper we introduce MAX-MIN Ant System, an improved version of basic Ant System, and report our results for its application to symmetric and asymmetric instances of the well known Traveling Salesman Problem. We show how MAX-MIN Ant System can be significantly improved extending it with local search heuristics. Our results clearly show that MAX-MIN Ant System has the property of effectively guiding the local search heuristics towards promising regions of the search space by generating good initial tours.
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页码:309 / 314
页数:6
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