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A Non-Parameter Filled Function Method for Unconstrained Global Optimization Problems

Author

Listed:
  • Yingchun Liu

    (School of Mathematics and Information Sciences, North Minzu University, Yinchuan 750021, P. R. China)

  • Yuelin Gao

    (Ningxia Province Cooperative Innovation Center of Scientific Computing and Intelligent Information Processing, North Minzu University, Yinchuan 750021, P. R. China)

  • Suxia Ma

    (School of Mathematics and Information Sciences, North Minzu University, Yinchuan 750021, P. R. China)

  • Eryang Guo

    (School of Mathematics and Information Sciences, North Minzu University, Yinchuan 750021, P. R. China)

Abstract

In the paper, we give a new non-parameter filled function method for finding global minimizer of global optimization programming problems, the filled function consists of a inverse cosine function and a logarithm function, and without parameter. Its theoretical residences are proved. A new filled function algorithm is given based on the proposed new parameterless filled function, The results of numerical with ten experiments verify the efficient and reliability for the algorithm.

Suggested Citation

  • Yingchun Liu & Yuelin Gao & Suxia Ma & Eryang Guo, 2024. "A Non-Parameter Filled Function Method for Unconstrained Global Optimization Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 41(02), pages 1-18, April.
    • Handle: RePEc:wsi:apjorx:v:41:y:2024:i:02:n:s0217595923500136
    DOI: 10.1142/S0217595923500136
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