Newton-type multilevel optimization method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F22%3A00532968" target="_blank" >RIV/67985556:_____/22:00532968 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.tandfonline.com/doi/full/10.1080/10556788.2019.1700256" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/10556788.2019.1700256</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/10556788.2019.1700256" target="_blank" >10.1080/10556788.2019.1700256</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Newton-type multilevel optimization method

Popis výsledku v původním jazyce

Inspired by multigrid methods for linear systems of equations, multilevel optimization methods have been proposed to solve structured optimization problems. Multilevel methods make more assumptions regarding the structure of the optimization model, and as a result, they outperform single-level methods, especially for large-scale models. The impressive performance of multilevel optimization methods is an empirical observation, and no theoretical explanation has so far been proposed. In order to address this issue, we study the convergence properties of a multilevel method that is motivated by second-order methods. We take the first step toward establishing how the structure of an optimization problem is related to the convergence rate of multilevel algorithms.

Název v anglickém jazyce

Newton-type multilevel optimization method

Popis výsledku anglicky

Inspired by multigrid methods for linear systems of equations, multilevel optimization methods have been proposed to solve structured optimization problems. Multilevel methods make more assumptions regarding the structure of the optimization model, and as a result, they outperform single-level methods, especially for large-scale models. The impressive performance of multilevel optimization methods is an empirical observation, and no theoretical explanation has so far been proposed. In order to address this issue, we study the convergence properties of a multilevel method that is motivated by second-order methods. We take the first step toward establishing how the structure of an optimization problem is related to the convergence rate of multilevel algorithms.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10101 - Pure mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Optimization Methods & Software

ISSN

1055-6788

e-ISSN

1029-4937

Svazek periodika

37

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

34

Strana od-do

45-78

Kód UT WoS článku

000502443800001

EID výsledku v databázi Scopus

2-s2.0-85076357344