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A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization

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  • Gaige Wang
  • Lihong Guo

Abstract

A novel robust hybrid metaheuristic optimization approach, which can be considered as an improvement of the recently developed bat algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of pitch adjustment operation in HS serving as a mutation operator during the process of the bat updating with the aim of speeding up convergence, thus making the approach more feasible for a wider range of real-world applications. The detailed implementation procedure for this improved metaheuristic method is also described. Fourteen standard benchmark functions are applied to verify the effects of these improvements, and it is demonstrated that, in most situations, the performance of this hybrid metaheuristic method (HS/BA) is superior to, or at least highly competitive with, the standard BA and other population-based optimization methods, such as ACO, BA, BBO, DE, ES, GA, HS, PSO, and SGA. The effect of the HS/BA parameters is also analyzed.

Suggested Citation

  • Gaige Wang & Lihong Guo, 2013. "A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-21, February.
    • Handle: RePEc:hin:jnljam:696491
    DOI: 10.1155/2013/696491
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    Cited by:

    1. Alaa Tharwat & Aboul Ella Hassanien, 2019. "Quantum-Behaved Particle Swarm Optimization for Parameter Optimization of Support Vector Machine," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 576-598, October.
    2. Kundan Kumar & Rajeev Arya, 2023. "A hybrid approach for cluster head determination of unmanned aerial vehicle in flying ad-hoc networks," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(3), pages 759-773, July.
    3. Gülnur Yildizdan & Ömer Kaan Baykan, 2020. "A New Hybrid BA_ABC Algorithm for Global Optimization Problems," Mathematics, MDPI, vol. 8(10), pages 1-36, October.
    4. Cheng-Long Wei & Gai-Ge Wang, 2020. "Hybrid Annealing Krill Herd and Quantum-Behaved Particle Swarm Optimization," Mathematics, MDPI, vol. 8(9), pages 1-23, August.

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