The DOI matches its Crossref record; 231 of the 231 references it cites were found in a registry or an index.
A review on genetic algorithm: past, present, and future
Open accessAbstract
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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“GA, derived from a study of a biological system, can solve both constrained and unconstrained optimization problems based on a natural selection process [164,165].”
From Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review (2021) · cites this paper as [165]
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Sorted by citations
Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review
Mohd Ghazali, M. H., & Rahiman, W. (2021) · Shock and Vibration · doi:10.1155/2021/9469318 · Cited by 249
“GA. GA, derived from a study of a biological system, can solve both constrained and unconstrained optimization problems based on a natural selection process [164, 165].”
BackgroundHassani, S., & Dackermann, U. (2023) · Sensors · doi:10.3390/s23063293 · Cited by 146
AI-driven design optimization for sustainable buildings: a systematic review
Manmatharasan, P., Bitsuamlak, G., & Grolinger, K. (2025) · Energy and Buildings · doi:10.1016/j.enbuild.2025.115440 · Cited by 63
Novel designs of blade mixer impellers from the discrete element method and topology optimization
Castro, M. T., & Ocon, J. D. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.151863 · Cited by 14
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Metadata
- Authors
- Katoch, S., Chauhan, S. S., & Kumar, V.
- Affiliations
- National Institute of Technology Hamirpur (BD)
- Corresponding author
- Kumar, Vijay
- ORCID
- Kumar, Vijay
- Venue
- Multimedia Tools and Applications
- Published
- 2020-10-31
- Volume
- 80
- Issue
- 5
- Pages
- 8091-8126
- ISSN
- 1380-7501 (ISSN-L)
- 1573-7721
- PMC
- PMC7599983
- OpenAlex
- W3094704314
- Cited by
- 4,655
- References
- 231
- Citations by year
- 2026: 596 · 2025: 1098 · 2024: 1173 · 2023: 1039 · 2022: 596 · 2021: 151 · 2020: 1
- FWCI
- 175.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Multimedia Tools and Applications (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Computer Science › Artificial Intelligence › Evolutionary Algorithms and Applications
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Antenna Design and Optimization
- Keywords
- genetic algorithm, genetic operators, fitness function, hybrid algorithm, evolutionary computation, future research directions
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