Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering

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 problems. These algorithms have been com...

Full description

Bibliographic Details
Main Authors: Fevrier Valdez, Oscar Castillo, Patricia Melin
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Algorithms
Subjects:
Online Access:https://www.mdpi.com/1999-4893/14/4/122
id doaj-34590a7451384619ad89dd6eb09832f1
record_format Article
spelling doaj-34590a7451384619ad89dd6eb09832f12021-04-13T19:07:28ZengMDPI AGAlgorithms1999-48932021-04-011412212210.3390/a14040122Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy ClusteringFevrier Valdez0Oscar Castillo1Patricia Melin2Division Graduate of Studies, Tijuana Institute of Technology, Calzada Tecnologico S/N, Tijuana 22414, MexicoDivision Graduate of Studies, Tijuana Institute of Technology, Calzada Tecnologico S/N, Tijuana 22414, MexicoDivision Graduate of Studies, Tijuana Institute of Technology, Calzada Tecnologico S/N, Tijuana 22414, MexicoIn 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 problems. These algorithms have been compared with the traditional ones and have demonstrated to be superior in many complex problems. This paper attempts to describe the algorithms based on nature, which are used in optimizing fuzzy clustering in real-world applications. We briefly describe the optimization methods, the most cited ones, nature-inspired algorithms that have been 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 area of nature and bio-inspired optimization of fuzzy clustering.https://www.mdpi.com/1999-4893/14/4/122fuzzyclusteringoptimization algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Fevrier Valdez
Oscar Castillo
Patricia Melin
spellingShingle Fevrier Valdez
Oscar Castillo
Patricia Melin
Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering
Algorithms
fuzzy
clustering
optimization algorithm
author_facet Fevrier Valdez
Oscar Castillo
Patricia Melin
author_sort Fevrier Valdez
title Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering
title_short Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering
title_full Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering
title_fullStr Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering
title_full_unstemmed Bio-Inspired Algorithms and Its Applications for Optimization in Fuzzy Clustering
title_sort bio-inspired algorithms and its applications for optimization in fuzzy clustering
publisher MDPI AG
series Algorithms
issn 1999-4893
publishDate 2021-04-01
description 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 problems. These algorithms have been compared with the traditional ones and have demonstrated to be superior in many complex problems. This paper attempts to describe the algorithms based on nature, which are used in optimizing fuzzy clustering in real-world applications. We briefly describe the optimization methods, the most cited ones, nature-inspired algorithms that have been 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 area of nature and bio-inspired optimization of fuzzy clustering.
topic fuzzy
clustering
optimization algorithm
url https://www.mdpi.com/1999-4893/14/4/122
work_keys_str_mv AT fevriervaldez bioinspiredalgorithmsanditsapplicationsforoptimizationinfuzzyclustering
AT oscarcastillo bioinspiredalgorithmsanditsapplicationsforoptimizationinfuzzyclustering
AT patriciamelin bioinspiredalgorithmsanditsapplicationsforoptimizationinfuzzyclustering
_version_ 1721528670771740672