期刊
INFORMATION SCIENCES
卷 295, 期 -, 页码 407-428出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2014.10.042
关键词
Large-Scale Global Optimization (LSGO); Evolutionary Algorithms (EAs); Cooperative Coevolution (CC); Problem decomposition; High-dimension; Metaheuristic
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. (C) 2014 Elsevier Inc. All rights reserved.
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