Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy
The impact of neutrosophy has increased rapidly in many areas of science and technology in recent years. Furthermore, numerous applications of the neutrosophic theory have become more usual. We aim to use neutrosophy to enhance Dai–Liao conjugate gradient (CG) iterative method. In particular, we sug...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/15/6/1217 |
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| author | Predrag S. Stanimirović Branislav D. Ivanov Dragiša Stanujkić Lev A. Kazakovtsev Vladimir N. Krutikov Darjan Karabašević |
| author_facet | Predrag S. Stanimirović Branislav D. Ivanov Dragiša Stanujkić Lev A. Kazakovtsev Vladimir N. Krutikov Darjan Karabašević |
| author_sort | Predrag S. Stanimirović |
| collection | DOAJ |
| description | The impact of neutrosophy has increased rapidly in many areas of science and technology in recent years. Furthermore, numerous applications of the neutrosophic theory have become more usual. We aim to use neutrosophy to enhance Dai–Liao conjugate gradient (CG) iterative method. In particular, we suggest and explore a new neutrosophic logic system intended to compute the essential parameter <i>t</i> required in Dai–Liao CG iterations. Theoretical examination and numerical experiments signify the effectiveness of the introduced method for controlling <i>t</i>. By incorporation of the neutrosophy in the Dai–Liao conjugate gradient principle, we established novel Dai–Liao CG iterations for solving large-scale unconstrained optimization problems. Global convergence is proved under standard assumptions and with the use of the inexact line search. Finally, computational evidence shows the computational effectiveness of the proposed fuzzy neutrosophic Dai–Liao CG method. |
| first_indexed | 2024-03-11T01:53:10Z |
| format | Article |
| id | doaj.art-818b044314eb414dadc9082b691bb6fe |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-11T01:53:10Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-818b044314eb414dadc9082b691bb6fe2023-11-18T12:51:05ZengMDPI AGSymmetry2073-89942023-06-01156121710.3390/sym15061217Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on NeutrosophyPredrag S. Stanimirović0Branislav D. Ivanov1Dragiša Stanujkić2Lev A. Kazakovtsev3Vladimir N. Krutikov4Darjan Karabašević5Faculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18000 Niš, SerbiaFaculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18000 Niš, SerbiaTechnical Faculty in Bor, University of Belgrade, Vojske Jugoslavije 12, 19210 Bor, SerbiaLaboratory “Hybrid Methods of Modelling and Optimization in Complex Systems”, Siberian Federal University, Prosp. Svobodny 79, 660041 Krasnoyarsk, RussiaDepartment of Applied Mathematics, Kemerovo State University, 6 Krasnaya Street, 650043 Kemerovo, RussiaFaculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, SerbiaThe impact of neutrosophy has increased rapidly in many areas of science and technology in recent years. Furthermore, numerous applications of the neutrosophic theory have become more usual. We aim to use neutrosophy to enhance Dai–Liao conjugate gradient (CG) iterative method. In particular, we suggest and explore a new neutrosophic logic system intended to compute the essential parameter <i>t</i> required in Dai–Liao CG iterations. Theoretical examination and numerical experiments signify the effectiveness of the introduced method for controlling <i>t</i>. By incorporation of the neutrosophy in the Dai–Liao conjugate gradient principle, we established novel Dai–Liao CG iterations for solving large-scale unconstrained optimization problems. Global convergence is proved under standard assumptions and with the use of the inexact line search. Finally, computational evidence shows the computational effectiveness of the proposed fuzzy neutrosophic Dai–Liao CG method.https://www.mdpi.com/2073-8994/15/6/1217neutrosophic logic systemsDai–Liao conjugate gradient methodbacktracking line searchconvergenceunconstrained optimization |
| spellingShingle | Predrag S. Stanimirović Branislav D. Ivanov Dragiša Stanujkić Lev A. Kazakovtsev Vladimir N. Krutikov Darjan Karabašević Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy Symmetry neutrosophic logic systems Dai–Liao conjugate gradient method backtracking line search convergence unconstrained optimization |
| title | Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy |
| title_full | Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy |
| title_fullStr | Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy |
| title_full_unstemmed | Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy |
| title_short | Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy |
| title_sort | fuzzy adaptive parameter in the dai liao optimization method based on neutrosophy |
| topic | neutrosophic logic systems Dai–Liao conjugate gradient method backtracking line search convergence unconstrained optimization |
| url | https://www.mdpi.com/2073-8994/15/6/1217 |
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