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Operations Research Transactions >

2025 , Vol. 29 >Issue 2: 141 - 157

DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2025.02.011

Research Article

A new non parameter-filled function method for global optimization

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  • 1. School of Mathematics and Information Sciences, North Minzu University, Yinchuan 750021, Ningxia, China
    2. College of Science, Jinling Institute of Technology, Nanjing 211169, Jiangsu, China
    3. School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, Ningxia, China

Received date: 2021-12-19

  Online published: 2025-06-12

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, 2025, All rights reserved. Unauthorized reproduction is prohibited.
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Abstract

The filled function method is a kind of deterministic method, which is adopted to find the global optimal solution for the unconstrained optimization problem. The core technique of this method is to construct the filled function, which is such that the iterative process of the algorithm constantly jump out of the current local minimizer. Currently, the filled function generally contains parameters, and the selection of parameters has a great influence on the computation effect of the algorithm. In this paper, a new non parameter-filled function is constructed by using the definition of filled function, and a new global optimization method is developed. Numerical experiments illustrate that this method is feasible and effective, and has better global optimization ability.

Key words： global optimization; unconstrained optimization problem; filled function method; non parameter

Cite this article

Suxia MA, Yuelin GAO, Hongwei LIN, Bo ZHANG . A new non parameter-filled function method for global optimization[J]. Operations Research Transactions, 2025 , 29(2) : 141 -157 . DOI: 10.15960/j.cnki.issn.1007-6093.2025.02.011

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