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• W2020009149 abstract "Three main streams of evolutionary algorithms (EAs), probabilistic optimization algorithms based on the model of natural evolution, are compared in this article: evolution strategies (ESs), evolutionary programming (EP), and genetic algorithms (GAs). The comparison is performed with respect to certain characteristic components of EAs: the representation scheme of object variables, mutation, recombination, and the selection operator. Furthermore, each algorithm is formulated in a high-level notation as an instance of the general, unifying basic algorithm, and the fundamental theoretical results on the algorithms are presented. Finally, after presenting experimental results for three test functions representing a unimodal and a multimodal case as well as a step function with discontinuities, similarities and differences of the algorithms are elaborated, and some hints to open research questions are sketched." @default.
• W2020009149 created "2016-06-24" @default.
• W2020009149 creator A5029781586 @default.
• W2020009149 creator A5062646838 @default.
• W2020009149 date "1993-03-01" @default.
• W2020009149 modified "2023-10-11" @default.
• W2020009149 title "An Overview of Evolutionary Algorithms for Parameter Optimization" @default.
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• W2020009149 doi "https://doi.org/10.1162/evco.1993.1.1.1" @default.
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