Abstract
In Differential Evolution, control parameters play important roles in balancing the exploration and exploitation capability, and different control parameters are required for different types of problems. However, finding optimal control parameters for each problem is difficult and not realistic. Hence, we propose a method to adjust them adaptively in this paper. In our proposed method, whether or not the current control parameters will be adjusted is based on a probability that is adaptively calculated according to their previous performance. Besides, normal distribution with variable mean value and standard deviation is employed to generate new control parameters. Performance on a set of benchmark functions indicates that our proposed method converges fast and achieves competitive results.
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Feng, L., Yang, YF., Wang, YX. (2008). A New Approach to Adapting Control Parameters in Differential Evolution Algorithm. In: Li, X., et al. Simulated Evolution and Learning. SEAL 2008. Lecture Notes in Computer Science, vol 5361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89694-4_3
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DOI: https://doi.org/10.1007/978-3-540-89694-4_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89693-7
Online ISBN: 978-3-540-89694-4
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