Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Fuzzy Adaptive Parameter in the Dai-Liao Optimization Method Based on Neutrosophy

Predrag Stanimirović
* ORCID logo ,
Branislav Ivanov
ORCID logo ,
Dragiša Stanujkić
ORCID logo ,
Lev Kazakovtsev
ORCID logo ,
Vladimir Krutikov
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Darjan Karabasevic
Version 1 : Received: 23 April 2023 / Approved: 24 April 2023 / Online: 24 April 2023 (12:43:01 CEST)

A peer-reviewed article of this Preprint also exists.

Stanimirović, P.S.; Ivanov, B.D.; Stanujkić, D.; Kazakovtsev, L.A.; Krutikov, V.N.; Karabašević, D. Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy. Symmetry 2023, 15, 1217. Stanimirović, P.S.; Ivanov, B.D.; Stanujkić, D.; Kazakovtsev, L.A.; Krutikov, V.N.; Karabašević, D. Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy. Symmetry 2023, 15, 1217.

Abstract

The influence of neutrosophy in the previous period is constantly growing in many areas of science and technology. Moreover, various applications of the neutrosophic approach have become more common in recent years. Our goal in this research is to utilize the neutrosophy to improve the performance of the Dai-Liao conjugate gradient (CG) method. Specifically, in this research, we propose and investigate a new neutrosophic logic system to calculate the key parameter t involved in the Dai–Liao CG iterations. Theoretical analysis and numerical experience indicate that the efficiency and robustness of the new rule for determining t. Combining the neutrosophy and the Dai-Liao conjugate gradient method, we propose and explore a new Dai-Liao CG iterations for solving large-scale unconstrained optimization models. The global convergence is established under common assumptions and the backtracking line search. Finally, by conducting numerical experiments, computational evidence demonstrates that the new fuzzy neutrosophic Dai-Liao conjugate gradient method is computationally effective and robust.

Keywords

Neutrosophic logic systems; Dai-Liao conjugate gradient method; Backtracking line search; Convergence; Unconstrained optimization.

Subject

Computer Science and Mathematics, Applied Mathematics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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