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A complex-valued encoding satin bowerbird optimization algorithm for global optimization

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Abstract

The real-valued satin bowerbird optimization (SBO) is a novel metaheuristic bio-inspired algorithm which imitates the ‘male-attracts-the-female for breeding’ principle of the specialized stick structure mechanism of satin birds. SBO has achieved success in congestion management, accurate software development effort estimation. In this paper, to enhance the SBO algorithm global exploration ability, a complex-valued encoding satin bowerbird optimization algorithm (CSBO) is proposed. We use complex-valued encoding enhance the diversity of the population, and the global exploration ability of the SBO algorithm. The proposed CSBO optimization algorithm is compared to SBO and other state-of-art optimization algorithms using ten benchmark functions. Simulation results show that the proposed CSBO can significantly improve the convergence accuracy and convergence speed of the original algorithm.

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Acknowledgements

This work is supported by National Science Foundation of China under Grants No. 61563008, and by Project of Guangxi Natural Science Foundation under Grant No. 2018GXNSFAA138146.

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Authors and Affiliations

  1. College of Information Science and Engineering, Guangxi University for Nationalities, Nanning, 530006, China

    Sen Zhang, Yongquan Zhou & Qifang Luo

  2. Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence, Nanning, 530006, China

    Yongquan Zhou & Qifang Luo

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  1. Sen Zhang
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  2. Yongquan Zhou
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  3. Qifang Luo
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Correspondence to Yongquan Zhou.

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Zhang, S., Zhou, Y. & Luo, Q. A complex-valued encoding satin bowerbird optimization algorithm for global optimization. Evolving Systems 12, 191–205 (2021). https://doi.org/10.1007/s12530-019-09307-3

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