Sequential Quadratic Programming Methods for Parametric Nonlinear Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00231893" target="_blank" >RIV/68407700:21230/14:00231893 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/article/10.1007%2Fs10589-014-9696-2" target="_blank" >http://link.springer.com/article/10.1007%2Fs10589-014-9696-2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10589-014-9696-2" target="_blank" >10.1007/s10589-014-9696-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sequential Quadratic Programming Methods for Parametric Nonlinear Optimization

Popis výsledku v původním jazyce

Sequential quadratic programming (SQP) methods are known to be efficient for solving a series of related nonlinear optimization problems because of desirable hot and warm start properties-a solution for one problem is a good estimate of the solution of the next. However, standard SQP solvers contain elements to enforce global convergence that can interfere with the potential to take advantage of these theoretical local properties in full. We present two new predictor-corrector procedures for solving a nonlinear program given a sufficiently accurate estimate of the solution of a similar problem. The procedures attempt to trace a homotopy path between solutions of the two problems, staying within the local domain of convergence for the series of problemsgenerated. We provide theoretical convergence and tracking results, as well as some numerical results demonstrating the robustness and performance of the methods.

Název v anglickém jazyce

Sequential Quadratic Programming Methods for Parametric Nonlinear Optimization

Popis výsledku anglicky

Sequential quadratic programming (SQP) methods are known to be efficient for solving a series of related nonlinear optimization problems because of desirable hot and warm start properties-a solution for one problem is a good estimate of the solution of the next. However, standard SQP solvers contain elements to enforce global convergence that can interfere with the potential to take advantage of these theoretical local properties in full. We present two new predictor-corrector procedures for solving a nonlinear program given a sufficiently accurate estimate of the solution of a similar problem. The procedures attempt to trace a homotopy path between solutions of the two problems, staying within the local domain of convergence for the series of problemsgenerated. We provide theoretical convergence and tracking results, as well as some numerical results demonstrating the robustness and performance of the methods.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

<a href="/cs/project/EE2.3.30.0034" target="_blank" >EE2.3.30.0034: Podpora zkvalitnění týmů výzkumu a vývoje a rozvoj intersektorální mobility na ČVUT v Praze</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název periodika

Computational Optimization and Applications

ISSN

0926-6003

e-ISSN

—

Svazek periodika

59

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

35

Strana od-do

475-509

Kód UT WoS článku

000344803000004

EID výsledku v databázi Scopus

2-s2.0-84926628059