The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Erratum: A Species Conserving Genetic Algorithm for Multimodal Function Optimization
Abstract
This paper introduces a new technique called species conservation for evolving parallel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current generation are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimization problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.
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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
Storn, R., & Price, K. (1997) · Journal of Global Optimization · doi:10.1023/a:1008202821328 · Cited by 29,569
Goldberg, D. E., & Shakespeare, W. (2002) · Cited by 16,088
Genetic Algorithms + Data Structures = Evolution Programs
Michalewicz, Z. (1992) · Artificial Intelligence · doi:10.1007/978-3-662-02830-8 · Cited by 11,553
Goldberg, D. E. (1989) · Medical Entomology and Zoology · Cited by 10,109
Glover, F. (1990) · ORSA Journal on Computing · doi:10.1287/ijoc.2.1.4 · Cited by 5,647
Genetic Algorithms and Engineering Design
Gen, M., & Cheng, R. (1996) · Wiley eBooks · doi:10.1002/9780470172254 · Cited by 2,460
Genetic algorithms with sharing for multimodal function optimization
Goldberg, D. E., & Richardson, J. T. (1987) · international conference on Genetic algorithms · Cited by 1,912
Eshelman, L. J. (1991) · Foundations of Genetic Algorithms · doi:10.1016/b978-0-08-050684-5.50020-3 · Cited by 1,040
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
Niching Without Niching Parameters: Particle Swarm Optimization Using a Ring Topology
Li, X. (2010) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2026270 · Cited by 466
Metadata
- Authors
- Li, J.-P., Balazs, M. E., Parks, G. T., & Clarkson, P. J.
- Venue
- Evolutionary Computation
- Publisher
- MIT Press
- Published
- 2003
- Volume
- 11
- Issue
- 1
- Pages
- 107-109
- ISSN
- 1063-6560 (ISSN-L)
- 1530-9304
- OpenAlex
- W1988383064
- Cited by
- 393
- References
- 20
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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