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Applied Computational Intelligence and Soft Computing
Volume 2010 (2010), Article ID 185063, 11 pages
Review Article

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 [7 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. View at Publisher · View at Google Scholar
  • 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. View at Publisher · View at Google Scholar
  • Ali Osman Kusakci, and Mehmet Can, “An Adaptive Penalty Based Covariance Matrix Adaptation-Evolution Strategy,” Computers & Operations Research, 2013. View at Publisher · View at Google Scholar
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  • 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. View at Publisher · View at Google Scholar
  • 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. View at Publisher · View at Google Scholar
  • Y. Diouane, S. Gratton, and L. N. Vicente, “Globally convergent evolution strategies for constrained optimization,” Computational Optimization and Applications, 2015. View at Publisher · View at Google Scholar