DIFFERENTIAL EVOLUTION WITH DYNAMIC ADAPTATION OF PARAMETERS BASED ON A FUZZY LOGIC AUGMENTATION APPROACH
Abstract
This paper proposes an improvement to the Differential Evolution algorithm using a fuzzy logic augmentation. The main contribution is to dynamically adapt the parameters of mutation (F) and crossover (CR) using a fuzzy system, with the aim that the fuzzy system calculates the optimal parameters of the differential evolution algorithm during execution for obtaining better solutions, in this way arriving to the proposed new fuzzy differential evolution algorithm. In this paper experiments are performed with a set of mathematical functions using the original algorithm and the proposed method. Based on a statistical comparison of the original and proposed method, we can state that the fuzzy differential evolution algorithm outperforms the original differential evolution method.
Keywords
References
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Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Publication Date
July 29, 2019
Submission Date
February 7, 2019
Acceptance Date
August 1, 2019
Published in Issue
Year 2019 Volume: 2 Number: 2