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International Work-Conference on Artificial Neural Networks

IWANN 2017: Advances in Computational Intelligence pp 62–72Cite as

Tuning of Clustering Search Based Metaheuristic by Cross-Validated Racing Approach

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10305))

Abstract

The success of a metaheuristic is directly tied to the good configuration of its free parameters, this process is called Tuning. However, this task is, usually, a tedious and laborious work without scientific robustness for almost all researches. The absence of a formal definition of the tuning and diversity of metaheuristic research contributes to the difficulty in comparing and validating the results, making the progress slower. In this paper, a tuning method named Cross-Validated Racing (CVR) is proposed along with the so named Biased Random-Key Evolutionary Clustering Search and applied to solve instances of the Permutation Flow Shop Problem (PFSP). The proposed approach has reached \(99.1\%\) of accuracy in predicting the optimal solution with the parameters found by Irace tuning method. Configurations generated by Irace, even different, have obtained results with the same statistical relevance.

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Acknowledgements

The authors would like to thank CNPq (grant 481845/2013-5) for partial funding of this research.

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Authors and Affiliations

  1. Universidade Federal do Maranho, Av. dos Portugueses, 1966 - Vila Bacanga, São Luís, MA, 65085-580, Brazil

    Thiago Henrique Lemos Fonseca & Alexandre Cesar Muniz de Oliveira

Authors
  1. Thiago Henrique Lemos Fonseca
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  2. Alexandre Cesar Muniz de Oliveira
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Corresponding author

Correspondence to Thiago Henrique Lemos Fonseca .

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Editors and Affiliations

  1. Universidad de Granada , Granada, Spain

    Ignacio Rojas

  2. University of Malaga , Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Barcelona, Spain

    Andreu Catala

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Fonseca, T.H.L., de Oliveira, A.C.M. (2017). Tuning of Clustering Search Based Metaheuristic by Cross-Validated Racing Approach. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2017. Lecture Notes in Computer Science(), vol 10305. Springer, Cham. https://doi.org/10.1007/978-3-319-59153-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-59153-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59152-0

  • Online ISBN: 978-3-319-59153-7

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