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A Joint Optimization Algorithm Based on the Optimal Shape Parameter–Gaussian Radial Basis Function Surrogate Model and Its Application

Author

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  • Jian Sun

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

  • Ling Wang

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

  • Dianxuan Gong

    (College of Science, North China University of Science and Technology, Tangshan 063210, China)

Abstract

We propose a joint optimization algorithm that combines the optimal shape parameter–Gaussian radial basis function (G-RBF) surrogate model with global and local optimization techniques to improve accuracy and reduce costs. We analyze factors that affect the accuracy of the G-RBF surrogate model and use the particle swarm optimization (PSO) algorithm to determine the optimal shape parameter and control the number and spacing of the sampling points for a high-precision surrogate model. Global optimization refines the surrogate model, serving as the initial value for local optimization to further refine the problem. Our experiments show that this method significantly reduces computation costs. We optimize the section size of cantilever beams for different materials, obtaining the optimal section size and mass for each. We find that hard aluminum alloy is the optimal choice, meeting yield strength and deflection requirements through finite element analysis verification. Our work highlights the effectiveness of the joint optimization algorithm based on the surrogate model, providing valuable tools and insights into optimizing various structures.

Suggested Citation

  • Jian Sun & Ling Wang & Dianxuan Gong, 2023. "A Joint Optimization Algorithm Based on the Optimal Shape Parameter–Gaussian Radial Basis Function Surrogate Model and Its Application," Mathematics, MDPI, vol. 11(14), pages 1-20, July.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:14:p:3169-:d:1197438
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    References listed on IDEAS

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    1. Xu, Shuhui & Wang, Yong & Wang, Zhi, 2019. "Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method," Energy, Elsevier, vol. 173(C), pages 457-467.
    2. Jian Sun & Ling Wang & Dianxuan Gong, 2023. "Model for Choosing the Shape Parameter in the Multiquadratic Radial Basis Function Interpolation of an Arbitrary Sine Wave and Its Application," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
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    Cited by:

    1. Ana Laura Mendonça Almeida Magalhães & Pedro Paiva Brito & Geraldo Pedro da Silva Lamon & Pedro Américo Almeida Magalhães Júnior & Cristina Almeida Magalhães & Pedro Henrique Mendonça Almeida Magalhãe, 2024. "Numerical Resolution of Differential Equations Using the Finite Difference Method in the Real and Complex Domain," Mathematics, MDPI, vol. 12(12), pages 1-39, June.

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