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A Parallel Swarm Library Based on Functional Programming Read chapter Read first chapter

2017 | OriginalPaper | Chapter

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

Authors : Thiago Henrique Lemos Fonseca, Alexandre Cesar Muniz de Oliveira

Published in: Advances in Computational Intelligence

Publisher: Springer International Publishing

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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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Metadata
Title
Tuning of Clustering Search Based Metaheuristic by Cross-Validated Racing Approach
Authors
Thiago Henrique Lemos Fonseca
Alexandre Cesar Muniz de Oliveira
Copyright Year
2017
Book
Advances in Computational Intelligence

Print ISBN: 978-3-319-59152-0

Electronic ISBN: 978-3-319-59153-7

Copyright Year: 2017

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

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