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The Scientific World Journal
Volume 2013, Article ID 378515, 11 pages
http://dx.doi.org/10.1155/2013/378515
Research Article

Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization

School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China

Received 9 September 2013; Accepted 17 October 2013

Academic Editors: T. Chen and J. Yang

Copyright © 2013 Peng Wang et al. 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.

  • Maurice Clerc, “Bibliography,” Guided Randomness in Optimization, pp. 285–291, 2015. View at Publisher · View at Google Scholar
  • Swamy, and Ke-Lin Dupp. 1–434, 2016. View at Publisher · View at Google Scholar
  • Ke-Lin Du, M. N. S. Swamy, Ke-Lin Du, and M. N. S. Swamy, “Swarm Intelligence,” Search and Optimization by Metaheuristics, pp. 237–263, 2016. View at Publisher · View at Google Scholar
  • Noria Bidi, and Zakaria Elberrichi, “Best Features Selection for Biomedical Data Classification Using Seven Spot Ladybird Optimization Algorithm,” International Journal of Applied Metaheuristic Computing, vol. 9, no. 3, pp. 75–87, 2018. View at Publisher · View at Google Scholar
  • Hao Qin, Feng Li, Zhaohong Liang, and Haochen Zhang, “Research on Energy-Storage Capacity Optimal Configuration Based on Scenario Analysis and Seven-spot Ladybird Optimization,” 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings, 2018. View at Publisher · View at Google Scholar
  • Nassima Dif, and Zakaria Elberrichi, “An enhanced recursive firefly algorithm for informative gene selection,” International Journal of Swarm Intelligence Research, vol. 10, no. 2, pp. 21–33, 2019. View at Publisher · View at Google Scholar