Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Exhaustive Review of Bio-Inspired Algorithms and its Applications for Optimization in Fuzzy Clustering

Version 1 : Received: 8 March 2021 / Approved: 10 March 2021 / Online: 10 March 2021 (13:17:09 CET)

A peer-reviewed article of this Preprint also exists.

Valdez, F.; Castillo, O.; Melin, P. Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering. Algorithms 2021, 14, 122. Valdez, F.; Castillo, O.; Melin, P. Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering. Algorithms 2021, 14, 122.

Journal reference: Algorithms 2021, 14, 122
DOI: 10.3390/a14040122

Abstract

In recent years, new metaheuristic algorithms have been developed taking as reference the inspiration on biological and natural phenomena. This nature-inspired approach for algorithm development has been widely used by many researchers in solving optimization problem. These algorithms have been compared with the traditional ones algorithms and have demonstrated to be superior in complex problems. This paper attempts to describe the algorithms based on nature, that are used in fuzzy clustering. We briefly describe the optimization methods, the most cited nature-inspired algorithms published in recent years, authors, networks and relationship of the works, etc. We believe the paper can serve as a basis for analysis of the new are of nature and bio-inspired optimization of fuzzy clustering.

Subject Areas

Fuzzy Logic; Clustering; optimization

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