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A review on genetic algorithm: past, present, and future
In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algor...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599983/ https://www.ncbi.nlm.nih.gov/pubmed/33162782 http://dx.doi.org/10.1007/s11042-020-10139-6 |
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author | Katoch, Sourabh Chauhan, Sumit Singh Kumar, Vijay |
author_facet | Katoch, Sourabh Chauhan, Sumit Singh Kumar, Vijay |
author_sort | Katoch, Sourabh |
collection | PubMed |
description | In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching. |
format | Online Article Text |
id | pubmed-7599983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-75999832020-11-02 A review on genetic algorithm: past, present, and future Katoch, Sourabh Chauhan, Sumit Singh Kumar, Vijay Multimed Tools Appl Article In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching. Springer US 2020-10-31 2021 /pmc/articles/PMC7599983/ /pubmed/33162782 http://dx.doi.org/10.1007/s11042-020-10139-6 Text en © Springer Science+Business Media, LLC, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Katoch, Sourabh Chauhan, Sumit Singh Kumar, Vijay A review on genetic algorithm: past, present, and future |
title | A review on genetic algorithm: past, present, and future |
title_full | A review on genetic algorithm: past, present, and future |
title_fullStr | A review on genetic algorithm: past, present, and future |
title_full_unstemmed | A review on genetic algorithm: past, present, and future |
title_short | A review on genetic algorithm: past, present, and future |
title_sort | review on genetic algorithm: past, present, and future |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599983/ https://www.ncbi.nlm.nih.gov/pubmed/33162782 http://dx.doi.org/10.1007/s11042-020-10139-6 |
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