期刊
SWARM AND EVOLUTIONARY COMPUTATION
卷 1, 期 2, 页码 61-70出版社
ELSEVIER
DOI: 10.1016/j.swevo.2011.05.001
关键词
Evolutionary computation; Surrogates; Meta-models; Machine learning; Expensive optimization problems; Model management
Surrogate-assisted, or meta-model based evolutionary computation uses efficient computational models, often known as surrogates or meta-models, for approximating the fitness function in evolutionary algorithms. Research on surrogate-assisted evolutionary computation began over a decade ago and has received considerably increasing interest in recent years. Very interestingly, surrogate-assisted evolutionary computation has found successful applications not only in solving computationally expensive single- or multi-objective optimization problems, but also in addressing dynamic optimization problems, constrained optimization problems and multi-modal optimization problems. This paper provides a concise overview of the history and recent developments in surrogate-assisted evolutionary computation and suggests a few future trends in this research area. (C) 2011 Elsevier B.V. All rights reserved.
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