The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index.
Parameter Control in Evolutionary Algorithms: Trends and Challenges
Abstract
More than a decade after the first extensive overview on parameter control, we revisit the field and present a survey of the state-of-the-art. We briefly summarize the development of the field and discuss existing work related to each major parameter or component of an evolutionary algorithm. Based on this overview, we observe trends in the area, identify some (methodological) shortcomings, and give recommendations for future research.
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Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
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
Self-organized criticality: An explanation of the 1/f noise
Bak, P., Tang, C., & Wiesenfeld, K. (1987) · Physical Review Letters · doi:10.1103/physrevlett.59.381 · Cited by 7,591
Introduction to Reinforcement Learning
Sutton, R. S., & Barto, A. G. (1998) · The MIT Press eBooks · Cited by 6,855
Global Sensitivity Analysis. The Primer
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2007) · doi:10.1002/9780470725184 · Cited by 6,430
Completely Derandomized Self-Adaptation in Evolution Strategies
Hansen, N., & Ostermeier, A. (2001) · Evolutionary Computation · doi:10.1162/106365601750190398 · Cited by 4,397
Introduction to Evolutionary Computing
Eiben, A. E., & Smith, J. E. (2003) · Natural Computing Series · doi:10.1007/978-3-662-05094-1 · Cited by 4,176
Self-citationJADE: Adaptive Differential Evolution With Optional External Archive
Zhang, J., & Sanderson, A. C. (2009) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2014613 · Cited by 3,739
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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
Karimi-Mamaghan, M., Mohammadi, M., Meyer, P., Karimi-Mamaghan, A. M., & Talbi, E.-G. (2022) · European Journal of Operational Research · doi:10.1016/j.ejor.2021.04.032 · Cited by 462
Ensemble of differential evolution variants
Wu, G., Shen, X., Li, H., Chen, H., Lin, A., & Suganthan, P. N. (2018) · Information Sciences · doi:10.1016/j.ins.2017.09.053 · Cited by 386
A Survey of Automatic Parameter Tuning Methods for Metaheuristics
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Metadata
- Authors
- Karafotias, G., Hoogendoorn, M., & Eiben, A. E.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2015-04
- Volume
- 19
- Issue
- 2
- Pages
- 167-187
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W2021027064
- Cited by
- 516
- References
- 103
- FWCI
- 30.04
- Type
- journal article
- Language
- en
- Open access
- closed
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