Abstract
This paper proposes a new variant of differential evolution for multimodal optimization termed DE/isolated/1. It generates new individuals close to an isolated individual in a current population as a niching scheme. This mechanism will evenly allocate search resources for each optimum. The proposed method was evaluated along with the existing methods through computational experiments using eight two-dimensional multimodal functions as benchmarks. Experimental results show that the proposed method shows better performance for several functions which are not effectively solved by existing algorithms.
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Otani, T., Suzuki, R., Arita, T. (2011). DE/isolated/1: A New Mutation Operator for Multimodal Optimization with Differential Evolution. In: Wang, D., Reynolds, M. (eds) AI 2011: Advances in Artificial Intelligence. AI 2011. Lecture Notes in Computer Science(), vol 7106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25832-9_33
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DOI: https://doi.org/10.1007/978-3-642-25832-9_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25831-2
Online ISBN: 978-3-642-25832-9
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