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Journal of Optimization
Volume 2017, Article ID 8042436, 7 pages
https://doi.org/10.1155/2017/8042436
Research Article

Improving the Fine-Tuning of Metaheuristics: An Approach Combining Design of Experiments and Racing Algorithms

1Brazilian Institute for Space Research (INPE), Cachoeira Paulista, SP, Brazil
2Universidade Estadual Paulista (UNESP), Guaratinguetá, SP, Brazil

Correspondence should be addressed to Eduardo Batista de Moraes Barbosa; rb.epni@asobrab.odraude

Received 10 February 2017; Accepted 10 April 2017; Published 7 June 2017

Academic Editor: Ferrante Neri

Copyright © 2017 Eduardo Batista de Moraes Barbosa and Edson Luiz França Senne. 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 [3 citations]

The following is the list of published articles that have cited the current article.

  • Erik Cuevas, Adolfo Reyna-Orta, and Margarita-Arimatea Díaz-Cortes, “A Multimodal Optimization Algorithm Inspired by the States of Matter,” Neural Processing Letters, 2017. View at Publisher · View at Google Scholar
  • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros, Erik Cuevas, Daniel Zaldívar, and Marco Pérez-Cisneros, “Multimodal States of Matter Search,” Advances in Metaheuristics Algorithms: Methods and Applications, vol. 775, pp. 119–165, 2018. View at Publisher · View at Google Scholar
  • Andrey Borisenko, and Sergei Gorlatch, “Optimizing a GPU-Parallelized Ant Colony Metaheuristic by Parameter Tuning,” Parallel Computing Technologies, vol. 11657, pp. 151–165, 2019. View at Publisher · View at Google Scholar