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A New Filled Function for Global Optimization Cover

Abstract

The filled function method has recently become very popular in optimization theory, as it is an e cient and e ective method for finding the global minimizer of multimodal functions. However, the fact that the existing filled functions in the literature generally have exponential or logarithmic terms and/or parameter sensitivity reduces the e ectiveness of this method. In this study, we propose a new non parameter and without exponential/logarithmic terms filled function, which is numerically stable, and is successfully used to solve global optimization problems. Furthermore, we have demonstrated how successful this new filled function method in terms of e ciency with numerical experiments and comparisons.

DOI: https://doi.org/10.2478/auom-2023-0039 | Journal eISSN: 1844-0835 | Journal ISSN: 1224-1784
Language: English
Page range: 207 - 220
Submitted on: Sep 23, 2022
Accepted on: Feb 14, 2023
Published on: Oct 21, 2023
Published by: Ovidius University of Constanta
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2023 Ahmet Şahiner, Temel Ermiş, Muhammad Wasim Awan, published by Ovidius University of Constanta
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.