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Hybridizing Harmony Search algorithm with different mutation operators for continuous problems

Author

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  • Hasan, Basima Hani F.
  • Abu Doush, Iyad
  • Al Maghayreh, Eslam
  • Alkhateeb, Faisal
  • Hamdan, Mohammad

Abstract

Harmony Search (HS) is a recent EA inspired by musical improvisation process to seek a pleasing harmony. Mutation is a vital component used in Evolutionary Algorithms (EA) where a value in the population is randomly selected to be altered to improve the evolution process. The original HS algorithm applies an operation similar to mutation during the random consideration operator. During random selection operator a value within the range of the decision variable is selected randomly to explore different areas in the search space. This paper aims at experimentally evaluating the performance of HS algorithm after replacing the random consideration operator in the original HS with five different mutation methods. The different variations of HS are experimented on standard benchmark functions in terms of final obtained solution and convergence speed. The results show that using polynomial mutation improves the performance of the HS algorithm for most of the used functions.

Suggested Citation

  • Hasan, Basima Hani F. & Abu Doush, Iyad & Al Maghayreh, Eslam & Alkhateeb, Faisal & Hamdan, Mohammad, 2014. "Hybridizing Harmony Search algorithm with different mutation operators for continuous problems," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 1166-1182.
    • Handle: RePEc:eee:apmaco:v:232:y:2014:i:c:p:1166-1182
    DOI: 10.1016/j.amc.2013.12.139
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    References listed on IDEAS

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    1. Deb, Kalyanmoy & Tiwari, Santosh, 2008. "Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1062-1087, March.
    2. Mohammed Al-Betar & Ahamad Khader, 2012. "A harmony search algorithm for university course timetabling," Annals of Operations Research, Springer, vol. 194(1), pages 3-31, April.
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    Cited by:

    1. Chen Zhang & Zhiwei Ni & Liping Ni & Na Tang, 2016. "Feature selection method based on multi-fractal dimension and harmony search algorithm and its application," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(14), pages 3476-3486, October.

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