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A New Method for Analyzing the Performance of the Harmony Search Algorithm

Author

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  • Shouheng Tuo

    (School of Computer Science and Technology, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
    Shaanxi Key Laboratory of Network Data Intelligent Processing, Xi’an University of Posts and Telecommunications, Xi’an 710121, China)

  • Zong Woo Geem

    (Department of Energy IT, Gachon University, Seongnam 13120, Korea)

  • Jin Hee Yoon

    (School of Mathematics and Statistics, Sejong University, Seoul 05006, Korea)

Abstract

A harmony search (HS) algorithm for solving high-dimensional multimodal optimization problems (named DIHS) was proposed in 2015 and showed good performance, in which a dynamic-dimensionality-reduction strategy is employed to maintain a high update success rate of harmony memory (HM). However, an extreme assumption was adopted in the DIHS that is not reasonable, and its analysis for the update success rate is not sufficiently accurate. In this study, we reanalyzed the update success rate of HS and now present a more valid method for analyzing the update success rate of HS. In the new analysis, take-k and take-all strategies that are employed to generate new solutions are compared to the update success rate, and the average convergence rate of algorithms is also analyzed. The experimental results demonstrate that the HS based on the take-k strategy is efficient and effective at solving some complex high-dimensional optimization problems.

Suggested Citation

  • Shouheng Tuo & Zong Woo Geem & Jin Hee Yoon, 2020. "A New Method for Analyzing the Performance of the Harmony Search Algorithm," Mathematics, MDPI, vol. 8(9), pages 1-17, August.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:9:p:1421-:d:403456
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    References listed on IDEAS

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    1. Yang Jiao & Jing Wu & Qing-kun Tan & Zhong-fu Tan & Guan Wang, 2017. "An Optimization Model and Modified Harmony Search Algorithm for Microgrid Planning with ESS," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-11, August.
    2. Shouheng Tuo & Longquan Yong & Fang’an Deng & Yanhai Li & Yong Lin & Qiuju Lu, 2017. "HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-23, April.
    3. FangAn Deng & Shouheng Tuo & Longquan Yong & Tao Zhou, 2015. "Construction Example for Algebra System Using Harmony Search Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-15, January.
    4. Shouheng Tuo & Junying Zhang & Xiguo Yuan & Yuanyuan Zhang & Zhaowen Liu, 2016. "FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-27, March.
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