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Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem. / Fominyh, Alexander.

Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings. ред. / Panos Pardalos; Michael Khachay; Vladimir Mazalov. Springer Nature, 2022. стр. 34-45 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 13367 LNCS).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Fominyh, A 2022, Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem. в P Pardalos, M Khachay & V Mazalov (ред.), Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 13367 LNCS, Springer Nature, стр. 34-45, 21st International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2022, Petrozavodsk, Российская Федерация, 2/07/22. https://doi.org/10.1007/978-3-031-09607-5_3

APA

Fominyh, A. (2022). Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem. в P. Pardalos, M. Khachay, & V. Mazalov (Ред.), Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings (стр. 34-45). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 13367 LNCS). Springer Nature. https://doi.org/10.1007/978-3-031-09607-5_3

Vancouver

Fominyh A. Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem. в Pardalos P, Khachay M, Mazalov V, Редакторы, Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings. Springer Nature. 2022. стр. 34-45. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-031-09607-5_3

Author

Fominyh, Alexander. / Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem. Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings. Редактор / Panos Pardalos ; Michael Khachay ; Vladimir Mazalov. Springer Nature, 2022. стр. 34-45 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{26edfee1b8a5486d833277b9d858a987,
title = "Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem",
abstract = "The paper considers a classical problem of calculus of variations with a nonsmooth integrand of the minimized functional. The integrand is assumed to be only subdifferentiable. Under some natural conditions the subdifferentiability of the functional considered is proved. The steepest (subdifferential) descent is found. Then the subdifferential descent method is applied to solve the initial problem. Some numerical examples demonstrate the algorithm implementation.",
keywords = "Nonsmooth variational problem, Subdifferential, Subdifferential descent method",
author = "Alexander Fominyh",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 21st International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2022 ; Conference date: 02-07-2022 Through 06-07-2022",
year = "2022",
doi = "10.1007/978-3-031-09607-5_3",
language = "English",
isbn = "9783031096068",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "34--45",
editor = "Panos Pardalos and Michael Khachay and Vladimir Mazalov",
booktitle = "Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings",
address = "Germany",
url = "http://motor2022.krc.karelia.ru/en/section/1",

}

RIS

TY - GEN

T1 - Application of the Subdifferential Descent Method to a Classical Nonsmooth Variational Problem

AU - Fominyh, Alexander

N1 - Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

PY - 2022

Y1 - 2022

N2 - The paper considers a classical problem of calculus of variations with a nonsmooth integrand of the minimized functional. The integrand is assumed to be only subdifferentiable. Under some natural conditions the subdifferentiability of the functional considered is proved. The steepest (subdifferential) descent is found. Then the subdifferential descent method is applied to solve the initial problem. Some numerical examples demonstrate the algorithm implementation.

AB - The paper considers a classical problem of calculus of variations with a nonsmooth integrand of the minimized functional. The integrand is assumed to be only subdifferentiable. Under some natural conditions the subdifferentiability of the functional considered is proved. The steepest (subdifferential) descent is found. Then the subdifferential descent method is applied to solve the initial problem. Some numerical examples demonstrate the algorithm implementation.

KW - Nonsmooth variational problem

KW - Subdifferential

KW - Subdifferential descent method

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UR - https://www.mendeley.com/catalogue/99c1e8d6-061d-3ccd-8a22-bfdcd55a97ed/

U2 - 10.1007/978-3-031-09607-5_3

DO - 10.1007/978-3-031-09607-5_3

M3 - Conference contribution

AN - SCOPUS:85134172502

SN - 9783031096068

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 34

EP - 45

BT - Mathematical Optimization Theory and Operations Research - 21st International Conference, MOTOR 2022, Proceedings

A2 - Pardalos, Panos

A2 - Khachay, Michael

A2 - Mazalov, Vladimir

PB - Springer Nature

T2 - 21st International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2022

Y2 - 2 July 2022 through 6 July 2022

ER -

ID: 97290678