The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
A clearing procedure as a niching method for genetic algorithms
Abstract
The clearing procedure is a niching method inspired by the principle stated by J.H. Holland (1975) - that of sharing limited resources within subpopulations of individuals characterized by some similarities - but instead of evenly sharing the available resources among the individuals of a subpopulation, the clearing procedure supplies these resources only to the best individuals of each subpopulation. The clearing is naturally adapted to elitist strategies. This can significantly improve the performance of genetic algorithms (GAs) applied to multimodal optimization. Moreover, the clearing procedure allows a GA to efficiently reduce the genetic drift when used with an appropriate selection operator. Some experimental results are presented for a massively multimodal deceptive function optimization.
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Cites
Genetic algorithms in search, optimization, and machine learning
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Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
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Genetic Algorithms in Search, Optimization & Machine Learning
Goldberg, D. E. (1989) · Medical Entomology and Zoology · Cited by 2,304
Genetic algorithms with sharing for multimodal function optimization
Goldberg, D. E., & Richardson, J. T. (1987) · international conference on Genetic algorithms · Cited by 1,912
Reducing bias and inefficiency in the selection algorithm
Baker, J. E. (1987) · international conference on Genetic algorithms · Cited by 1,415
(1991) · Lecture Notes in Computer Science · doi:10.1007/bfb0029723 · Cited by 1,049
Niching methods for genetic algorithms
Mahfoud, S. W. (1996) · Cited by 897
Cited by
Differential Evolution: A Survey of the State-of-the-Art
Das, S., & Suganthan, P. N. (2011) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2010.2059031 · Cited by 5,307
Exploration and exploitation in evolutionary algorithms: A survey
Črepinšek, M., Liu, S.-H., & Mernik, M. (2013) · ACM Computing Surveys · doi:10.1145/2480741.2480752 · Cited by 1,298
Bio-inspired computation: Where we stand and what's next
Del Ser, J., Osaba, E., Molina, D., Yang, X.-S., Salcedo-Sanz, S., Camacho, D., Das, S., Suganthan, P. N., Coello Coello, C. A., & Herrera, F. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2019.04.008 · Cited by 593
Yue, C., Qu, B., & Liang, J. (2018) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2017.2754271 · Cited by 585
Fitness sharing and niching methods revisited
Sareni, B., & Krahenbuhl, L. (1998) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.735432 · Cited by 578
Metadata
- Authors
- Petrowski, A.
- Venue
- Proceedings of IEEE International Conference on Evolutionary Computation ICEC-96
- Publisher
- IEEE
- Published
- 1996
- Pages
- 798-803
- OpenAlex
- W2132147811
- Cited by
- 630
- References
- 8
- FWCI
- 2.75
- Type
- conference paper
- Language
- en
- Open access
- closed
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