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CQND-WHO: chaotic quantum nonlinear differential wild horse optimizer

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Abstract

Wild horse optimizer (WHO) features a simple structure with few parameters, facilitating fast convergence. However, it suffers from low global search efficiency and struggles to escape local optima during late-stage re-evolution. To address WHO’s underutilization of individuals within the population, a quantum-accelerated search algorithm was developed to enhance individual search capabilities. Moreover, a global perturbation strategy based on chaotic mapping was introduced to overcome the challenge of escaping local optima. To improve the algorithm's search efficiency, an adaptive evolution strategy was formulated. Finally, introduce the novel hybrid optimization algorithm, named chaotic quantum nonlinear differential wild horse optimizer (CQND-WHO). In this study, we tested CQND-WHO using 23 classical test suites, the CEC2014 and CEC2017 benchmarks. The results demonstrate that the improved strategy effectively addresses WHO's shortcomings. Furthermore, when compared to other optimization algorithms considered in this study, CQND-WHO exhibits significantly enhanced convergence accuracy and efficiency in solving high-dimensional complex multi-peak problems, offering a novel approach to addressing multidimensional complex multi-peak problems.

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Funding

The work is supported by the following project grants, Heilongjiang Excellent Youth Fund Project (YQ2021E015); Natural Science Foundation of Heilongjiang Province of China (ZD2022E002); Hainan Province’s Key Research and Development Project (ZDYF2023GXJS017); National Natural Science Foundation of China (No.51509056); National Science and Technology Council, Taiwan (MOST 111-2410-H161-001).

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Authors and Affiliations

  1. College of Shipbuilding Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang, China

    Ming-Wei Li, Yu-Tian Wang & Xiang-Yang Li

  2. NanHai Institute of Harbin Engineering University, Harbin Engineering University, Sanya, 572024, HaiNan, China

    Ming-Wei Li

  3. School of Economics and Management, Harbin Engineering University, Harbin, 150001, Heilongjiang, China

    Zhong-Yi Yang

  4. Department of Information Management, Chihlee University of Technology, 313, Sec. 1, Wenhua Rd., Banqiao Dist., New Taipei, 220305, Taiwan

    Hsin-Pou Huang

  5. Department of Information Management, Asia Eastern University of Science and Technology, 58, Sec. 2, Sichuan Rd., Banqiao Dist., New Taipei, 22046, Taiwan

    Wei-Chiang Hong

  6. Department of Information Management, Yuan Ze University, 135, Yuandong Rd., Zhongli Dist., Taoyuan City, 320315, Taiwan

    Wei-Chiang Hong

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  1. Ming-Wei Li
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Li, MW., Wang, YT., Yang, ZY. et al. CQND-WHO: chaotic quantum nonlinear differential wild horse optimizer. Nonlinear Dyn 112, 4899–4927 (2024). https://doi.org/10.1007/s11071-023-09246-4

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