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Algorithms 2017, 10(1), 18; doi:10.3390/a10010018

Imperialist Competitive Algorithm with Dynamic Parameter Adaptation Using Fuzzy Logic Applied to the Optimization of Mathematical Functions

Tijuana Institute of Technology, Tijuana 22379, Mexico
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Academic Editors: Yun-Chia Liang and Toly Chen
Received: 28 September 2016 / Revised: 4 January 2017 / Accepted: 16 January 2017 / Published: 23 January 2017
(This article belongs to the Special Issue Metaheuristic Algorithms in Optimization and Applications)
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Abstract

In this paper we are presenting a method using fuzzy logic for dynamic parameter adaptation in the imperialist competitive algorithm, which is usually known by its acronym ICA. The ICA algorithm was initially studied in its original form to find out how it works and what parameters have more effect upon its results. Based on this study, several designs of fuzzy systems for dynamic adjustment of the ICA parameters are proposed. The experiments were performed on the basis of solving complex optimization problems, particularly applied to benchmark mathematical functions. A comparison of the original imperialist competitive algorithm and our proposed fuzzy imperialist competitive algorithm was performed. In addition, the fuzzy ICA was compared with another metaheuristic using a statistical test to measure the advantage of the proposed fuzzy approach for dynamic parameter adaptation. View Full-Text
Keywords: imperialist competitive algorithm; fuzzy logic; dynamic adjust imperialist competitive algorithm; fuzzy logic; dynamic adjust
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Bernal, E.; Castillo, O.; Soria, J.; Valdez, F. Imperialist Competitive Algorithm with Dynamic Parameter Adaptation Using Fuzzy Logic Applied to the Optimization of Mathematical Functions. Algorithms 2017, 10, 18.

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