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...

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Published in	Multimedia tools and applications Vol. 80; no. 5; pp. 8091 - 8126
Main Authors	Katoch, Sourabh, Chauhan, Sumit Singh, Kumar, Vijay
Format	Journal Article
Language	English
Published	New York Springer US 01.02.2021 Springer Nature B.V
Subjects	Computer Communication Networks Computer Science Data Structures and Information Theory Genetic algorithms Multimedia Information Systems Operators Special Purpose and Application-Based Systems Metaheuristic Genetic algorithm Selection Evolution Mutation Crossover Optimization
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Abstract	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.
AbstractList	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. 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.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.
Author	Katoch, Sourabh Chauhan, Sumit Singh Kumar, Vijay
Author_xml	– sequence: 1 givenname: Sourabh surname: Katoch fullname: Katoch, Sourabh organization: Computer Science and Engineering Department, National Institute of Technology – sequence: 2 givenname: Sumit Singh surname: Chauhan fullname: Chauhan, Sumit Singh organization: Computer Science and Engineering Department, National Institute of Technology – sequence: 3 givenname: Vijay orcidid: 0000-0002-3460-6989 surname: Kumar fullname: Kumar, Vijay email: vijaykumarchahar@gmail.com organization: Computer Science and Engineering Department, National Institute of Technology
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33162782$$D View this record in MEDLINE/PubMed
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Keywords	Metaheuristic Genetic algorithm Selection Evolution Mutation Crossover Optimization
Language	English
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Snippet	In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected...
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SubjectTerms	Computer Communication Networks Computer Science Data Structures and Information Theory Genetic algorithms Multimedia Information Systems Operators Special Purpose and Application-Based Systems
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Title	A review on genetic algorithm: past, present, and future
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