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A hybrid PBIL-based harmony search method

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Abstract

The harmony search (HS) method is a popular meta-heuristic optimization algorithm, which has been extensively employed to handle various engineering problems. However, it sometimes fails to offer a satisfactory convergence performance under certain circumstances. In this paper, we propose and study a hybrid HS approach, HS–PBIL, by merging the HS together with the population-based incremental learning (PBIL). Numerical simulations demonstrate that our HS–PBIL is well capable of outperforming the regular HS method in dealing with nonlinear function optimization and a practical wind generator optimization problem.

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Acknowledgments

This research work was funded by the project FOVI that is part of FIMECC-program EFFIMA and Academy of Finland under Grants 137837, 135225, and 127299. The authors would like to thank the anonymous reviewers for their insightful comments and constructive suggestions that have improved the paper.

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Authors and Affiliations

  1. Department of Automation and Systems Technology, Aalto University School of Electrical Engineering, Otaniementie 17, 00076, Aalto, Finland

    X. Z. Gao, X. Wang & K. Zenger

  2. Department of Electrical Engineering, Aalto University School of Electrical Engineering, Otakaari 5 A, 00076, Aalto, Finland

    T. Jokinen, S. J. Ovaska & A. Arkkio

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  1. X. Z. Gao
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  2. X. Wang
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  3. T. Jokinen
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  4. S. J. Ovaska
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  5. A. Arkkio
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  6. K. Zenger
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Correspondence to X. Z. Gao.

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Gao, X.Z., Wang, X., Jokinen, T. et al. A hybrid PBIL-based harmony search method. Neural Comput & Applic 21, 1071–1083 (2012). https://doi.org/10.1007/s00521-011-0675-6

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  • DOI: https://doi.org/10.1007/s00521-011-0675-6

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