Smoothing Levenberg-Marquardt algorithm for solving non-Lipschitz absolute value equations
Journal of Applied Analysis, cilt.29, sa.2, ss.277-286, 2023 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 29 Sayı: 2
- Basım Tarihi: 2023
- Doi Numarası: 10.1515/jaa-2022-1025
- Dergi Adı: Journal of Applied Analysis
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, ABI/INFORM, zbMATH
- Sayfa Sayıları: ss.277-286
- Anahtar Kelimeler: Non-Lipschitz absolute value equations, smoothing techniques, Levenberg-Marquardt algorithm, GENERALIZED NEWTON METHOD, NEURAL-NETWORK, VERTICAL-BAR, COMPLEMENTARITY, NONSMOOTH
- Süleyman Demirel Üniversitesi Adresli: Evet
Özet
© 2023 Walter de Gruyter GmbH, Berlin/Boston 2023.In this study, we concentrate on solving the problem of non-Lipschitz absolute value equations (NAVE). A new Bezier curve based smoothing technique is introduced and a new Levenberg-Marquardt type algorithm is developed depending on the smoothing technique. The numerical performance of the algorithm is analysed by considering some well-known and randomly generated test problems. Finally, the comparison with other methods is illustrated to demonstrate the efficiency of the proposed algorithm.