2009•Unpublished venueRequires access

Dynamic optimization using Self-Adaptive Differential Evolution

Janez Brest, Aleš Zamuda, Borko Boškovič, Mirjam Sepesy Maučec, Viljem Zumer

Open publisher page 173 citations

Abstract

In this paper we investigate a Self-Adaptive Differential Evolution algorithm (jDE) where F and CR control parameters are self-adapted and a multi-population method with aging mechanism is used. The performance of the jDE algorithm is evaluated on the set of benchmark functions provided for the CEC 2009 special session on evolutionary computation in dynamic and uncertain environments.

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What this paper is about

In this paper we investigate a Self-Adaptive Differential Evolution algorithm (jDE) where F and CR control parameters are self-adapted and a multi-population method with aging mechanism is used. The performance of the jDE algorithm is evaluated on the set of benchmark functions provided for the CEC 2009 special session on evolutionary computation in dynamic and uncertain environments.

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OpenAlex reports 173 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper we investigate a Self-Adaptive Differential Evolution algorithm (jDE) where F and CR control parameters are self-adapted and a multi-population method with aging mechanism is used. The performance of the jDE algorithm is evaluated on the set of benchmark functions provided for the CEC 2009 special session on evolutionary computation in dynamic and uncertain environments.

Key concepts: Differential evolution, Evolutionary computation, Benchmark (surveying), Computer science, Computation, Evolutionary algorithm, Mathematical optimization, Set (abstract data type)

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