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Revised Gravitational Search Algorithms Based on Evolutionary-Fuzzy Systems

Department of Communication Sciences, University of Teramo, 64100 Teramo, Italy
Author to whom correspondence should be addressed.
Algorithms 2017, 10(2), 44;
Received: 25 January 2017 / Revised: 4 April 2017 / Accepted: 18 April 2017 / Published: 21 April 2017
(This article belongs to the Special Issue Extensions to Type-1 Fuzzy Logic: Theory, Algorithms and Applications)
PDF [400 KB, uploaded 24 April 2017]


The choice of the best optimization algorithm is a hard issue, and it sometime depends on specific problem. The Gravitational Search Algorithm (GSA) is a search algorithm based on the law of gravity, which states that each particle attracts every other particle with a force called gravitational force. Some revised versions of GSA have been proposed by using intelligent techniques. This work proposes some GSA versions based on fuzzy techniques powered by evolutionary methods, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE), to improve GSA. The designed algorithms tune a suitable parameter of GSA through a fuzzy controller whose membership functions are optimized by GA, PSO and DE. The results show that Fuzzy Gravitational Search Algorithm (FGSA) optimized by DE is optimal for unimodal functions, whereas FGSA optimized through GA is good for multimodal functions. View Full-Text
Keywords: gravitational search algorithm; fuzzy systems; evolutionary algorithm gravitational search algorithm; fuzzy systems; evolutionary algorithm

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Pelusi, D.; Mascella, R.; Tallini, L. Revised Gravitational Search Algorithms Based on Evolutionary-Fuzzy Systems. Algorithms 2017, 10, 44.

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