Metaheuristics in large-scale global continues optimization: A survey.

Information Sciences(2015)

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摘要
Metaheuristic algorithms are extensively recognized as effective approaches for solving high-dimensional optimization problems. These algorithms provide effective tools with important applications in business, engineering, economics, and science. This paper surveys state-of-the-art metaheuristic algorithms and their current applications in the field of large-scale global optimization. The paper mainly covers the fundamental algorithmic frameworks such as decomposition and non-decomposition methods. More than 200 papers are carefully reviewed to prepare the current comprehensive survey.
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关键词
Large-Scale Global Optimization (LSGO),Evolutionary Algorithms (EAs),Cooperative Coevolution (CC),Problem decomposition,High-dimension,Metaheuristic
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