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

Yingchun Liu (), Yuelin Gao, Suxia Ma () and Eryang Guo ()
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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

Asia-Pacific Journal of Operational Research (APJOR), 2024, vol. 41, issue 02, 1-18

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.

Keywords: Global optimization problems; filled function; deterministic algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0217595923500136

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