Abstract
Large-scale global optimization (LSGO) is a very important and challenging task in optimization domain, which is embedded in many scientific and engineering applications. Previously, the cooperative co-evolution (CC) is a usual and effective choice for LSGO problems. In this paper, aim at more fully exploring the flexibility and potential of CC strategy, an adaptive CC (ACC) is designed to handle LSGO problems. The advantages of ACC compared with the classical CC strategies are experimentally verified on a set of widely used large scale function optimization problems.
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