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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Veröffentlicht in:Multimedia tools and applications Jg. 80; H. 5; S. 8091 - 8126
Hauptverfasser: Katoch, Sourabh, Chauhan, Sumit Singh, Kumar, Vijay
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.02.2021
Springer Nature B.V
Schlagworte:
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
ISSN:1380-7501, 1573-7721
Online-Zugang:Volltext
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Zusammenfassung: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.
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ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-020-10139-6