Autonomous operator management for evolutionary algorithms

作     者：Maturana, Jorge Lardeux, Frederic Saubion, Frederic 

作者机构：Univ Austral Chile Inst Informat Valdivia 5111187 Chile Univ Angers Lab LERIA Dept Informat UFR Sci F-49045 Angers France 

出 版 物：《JOURNAL OF HEURISTICS》 (试探法杂志)

年 卷 期：2010年第16卷第6期

页      面：881-909页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Parameter control Adaptive search Hyper-heuristics Algorithm design 

摘      要：The performance of an evolutionary algorithm strongly depends on the design of its operators and on the management of these operators along the search;that is, on the ability of the algorithm to balance exploration and exploitation of the search space. Recent approaches automate the tuning and control of the parameters that govern this balance. We propose a new technique to dynamically control the behavior of operators in an EA and to manage a large set of potential operators. The best operators are rewarded by applying them more often. Tests of this technique on instances of 3-SAT return results that are competitive with an algorithm tailored to the problem.