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Enhanced harmony search with dual strategies and adaptive parameters

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Abstract

Harmony search (HS) is an emerging approach for global optimization. However, HS often demonstrates insufficient convergence due to the weak exploitation capability of its search strategy. Concerning this weakness, an enhanced HS with dual strategies and adaptive parameters (DSAHS) is proposed. In its search process, DSAHS conducts the best harmony-guided and random harmony-guided search strategies to balance the exploration and exploitation capabilities. Moreover, DSAHS adaptively adjusts its major parameters in the light of the heuristic information from the search procedure. Experiments and comparisons based on a suit of well-known test functions indicate that DSAHS achieves competitive results on the most of the test functions.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Nos. 61662029 and 41561091) and the Natural Science Foundation of Jiangxi, China (No. 20151BAB217010).

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Authors and Affiliations

  1. School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, 510006, China

    Yong Wang

  2. School of Science, JiangXi University of Science and Technology, Ganzhou, 341000, China

    Zhaolu Guo & Yang Wang

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  1. Yong Wang
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  2. Zhaolu Guo
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  3. Yang Wang
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Correspondence to Zhaolu Guo.

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Communicated by V. Loia.

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Wang, Y., Guo, Z. & Wang, Y. Enhanced harmony search with dual strategies and adaptive parameters. Soft Comput 21, 4431–4445 (2017). https://doi.org/10.1007/s00500-017-2563-1

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