Model-Based Search for Combinatorial Optimization: A Critical Survey

被引：0
|
作者：
Mark Zlochin
Mauro Birattari
Nicolas Meuleau
Marco Dorigo
机构：
[1] The Weizmann Institute of Science,Dept. of Applied Mathematics and Computer Science
[2] Université Libre de Bruxelles,IRIDIA
[3] NASA Ames Research Center,undefined
来源：
Annals of Operations Research | 2004年 / 131卷
关键词：
ant colony optimization; cross-entropy method; stochastic gradient ascent; estimation of distribution algorithms; adaptive optimization; metaheuristics;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper we introduce model-based search as a unifying framework accommodating some recently proposed metaheuristics for combinatorial optimization such as ant colony optimization, stochastic gradient ascent, cross-entropy and estimation of distribution methods. We discuss similarities as well as distinctive features of each method and we propose some extensions.
引用
收藏
页码：373 / 395
页数：22
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