The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Comparative review of selection techniques in genetic algorithm
Abstract
This paper compares various selection techniques used in Genetic Algorithm. Genetic algorithms are optimization search algorithms that maximize or minimizes given functions. Indentifying the appropriate selection technique is a critical step in genetic algorithm. The process of selection plays an important role in resolving premature convergence because it occurs due to lack of diversity in the population. Therefore selection of population in each generation is very important. In this study, we have reported the significant work conducted on various selection techniques and the comparison of selection techniques.
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Cites
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,010
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Genetic Algorithms in Search, Optimization and Machine Learning
Goldberg, D. E., & Robson, D. (1988) · Cited by 18,391
A Comparative Analysis of Selection Schemes Used in Genetic Algorithms
Goldberg, D. E., & Deb, K. (1991) · Foundations of Genetic Algorithms · doi:10.1016/b978-0-08-050684-5.50008-2 · Cited by 2,407
Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization
Mühlenbein, H., & Schlierkamp-Voosen, D. (1993) · Evolutionary Computation · doi:10.1162/evco.1993.1.1.25 · Cited by 1,199
Adaptive Selection Methods for Genetic Algorithms
Baker, J. E. (1985) · international conference on Genetic algorithms · Cited by 1,022
Genetic algorithms in engineering electromagnetics
Johnson, J. M., & Rahmat-Samii, V. (1997) · IEEE Antennas and Propagation Magazine · doi:10.1109/74.632992 · Cited by 890
Genetic Algorithm Performance with Different Selection Strategies in Solving TSP
Razali, N. M., & Geraghty, J. (2011) · Cited by 359
A comparative review of approaches to prevent premature convergence in GA
Pandey, H. M., Chaudhary, A., & Mehrotra, D. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.08.025 · Cited by 279
Self-citationComparison of Performance between Different Selection Strategies on Simple Genetic Algorithms
Zhong, J., Hu, X.-M., Zhang, J., & Gu, M. H. (2006) · doi:10.1109/cimca.2005.1631619 · Cited by 164
Cited by
Choosing Mutation and Crossover Ratios for Genetic Algorithms—A Review with a New Dynamic Approach
Hassanat, A., Almohammadi, K., Alkafaween, E., Abunawas, E., Hammouri, A., & Prasath, V. B. S. (2019) · Information · doi:10.3390/info10120390 · Cited by 668
Linder, J., Bogard, N., Rosenberg, A. B., & Seelig, G. (2020) · Cell Systems · doi:10.1016/j.cels.2020.05.007 · Cited by 107
Metadata
- Authors
- Shukla, A., Pandey, H. M., & Mehrotra, D.
- Venue
- 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE)
- Publisher
- IEEE
- Published
- 2015-02
- Pages
- 515-519
- OpenAlex
- W1499536210
- Cited by
- 259
- References
- 10
- FWCI
- 4.92
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Shukla, A., Pandey, H. M., & Mehrotra, D. (2015). Comparative review of selection techniques in genetic algorithm. 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE). https://doi.org/10.1109/ablaze.2015.7154916
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