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Applied Computational Intelligence and Soft Computing
Volume 2010 (2010), Article ID 185063, 11 pages
A Review of Constraint-Handling Techniques for Evolution Strategies
International Computer Science Institute, Berkeley, CA 94704, USA
Received 24 September 2009; Accepted 6 January 2010
Academic Editor: Chuan-Kang Ting
Copyright © 2010 Oliver Kramer. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citations to this Article [6 citations]
The following is the list of published articles that have cited the current article.
- Efrén Mezura-Montes, and Carlos A. Coello Coello, “Constraint-handling in nature-inspired numerical optimization: Past, present and future,” Swarm and Evolutionary Computation, vol. 1, no. 4, pp. 173–194, 2011.
- Liang Gao, Jida Huang, and Xinyu Li, “An effective cellular particle swarm optimization for parameters optimization of a multi-pass milling process,” Applied Soft Computing, vol. 12, no. 11, pp. 3490–3499, 2012.
- Ali Osman Kusakci, and Mehmet Can, “An Adaptive Penalty Based Covariance Matrix Adaptation-Evolution Strategy,” Computers & Operations Research, 2013.
- Saber M. Elsayed, Ruhul A. Sarker, and Daryl L. Essam, “Adaptive Configuration of evolutionary algorithms for constrained optimization,” Applied Mathematics and Computation, vol. 222, pp. 680–711, 2013.
- Michael Sonnenschein, Ontje Lünsdorf, Jörg Bremer, and Martin Tröschel, “Decentralized control of units in smart grids for the support of renewable energy supply,” Environmental Impact Assessment Review, 2014.
- Qiang Long, and Changzhi Wu, “A hybrid method combining genetic algorithm and Hooke-Jeeves method for constrained global optimization,” Journal of Industrial and Management Optimization, vol. 10, no. 4, pp. 1279–1296, 2014.