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Erschienen in:
2009 | OriginalPaper | Buchkapitel
An Adaptive Parameter Control for the Differential Evolution Algorithm
verfasst von : Gilberto Reynoso-Meza, Javier Sanchis, Xavier Blasco
Erschienen in: Bio-Inspired Systems: Computational and Ambient Intelligence
Verlag: Springer Berlin Heidelberg
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The Differential Evolution is a floating-point evolutionary algorithm that has demonstrated good performance on locating the global optima in a wide variety of problems and applications. It has mainly three tuning parameters and their choice is fundamental to ensure good quality solutions. Because of this, adaptive parameter control and self-adaptive parameter control had been object of research. We present a novel scheme for controlling two parameters of the Differential Evolution using fitness information of the population in each generation. The algorithm shows outstanding performance on a well known benchmark functions, improving the standard DE and comparable with similar algorithms.