Abstract
In this paper, we present an empirical study on convergence nature of Differential Evolution (DE) variants to solve unconstrained global optimization problems. The aim is to identify the convergence behavior of DE variants and compare. We have chosen fourteen benchmark functions grouped by feature: unimodal separable, unimodal nonseparable, multimodal separable and multimodal nonseparable. Fourteen variants of DE were implemented and tested on these problems for dimensions of 30. The variants are well compared by their Convergence Speed, Quality Measure and Population Convergence Measure.
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Jeyakumar, G., Shanmugavelayutham, C. (2011). Empirical Measurements on the Convergence Nature of Differential Evolution Variants. In: Meghanathan, N., Kaushik, B.K., Nagamalai, D. (eds) Advances in Computer Science and Information Technology. CCSIT 2011. Communications in Computer and Information Science, vol 131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17857-3_46
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DOI: https://doi.org/10.1007/978-3-642-17857-3_46
Publisher Name: Springer, Berlin, Heidelberg
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