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Stabilized Sequential Quadratic Programming for Optimization and a Stabilized Newton-type Method for Variational Problems Without Constraint Qualifications
Language: en
Pages: 23

Stabilized Sequential Quadratic Programming for Optimization and a Stabilized Newton-type Method for Variational Problems Without Constraint Qualifications

Authors: Damián Fernández
Categories:
Type: BOOK - Published: 2007 - Publisher:

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Newton-Type Methods for Optimization and Variational Problems
Language: en
Pages: 587

Newton-Type Methods for Optimization and Variational Problems

Authors: Alexey F. Izmailov
Categories: Business & Economics
Type: BOOK - Published: 2014-07-08 - Publisher: Springer

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This book presents comprehensive state-of-the-art theoretical analysis of the fundamental Newtonian and Newtonian-related approaches to solving optimization and
Stabilized Sequential Quadratic Programming for Optimization and a Stabilized Newton-type Method for Variational Problems
Language: en
Pages:

Stabilized Sequential Quadratic Programming for Optimization and a Stabilized Newton-type Method for Variational Problems

Authors: Damián Fernández
Categories:
Type: BOOK - Published: 2007 - Publisher:

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Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition
Language: en
Pages: 995

Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition

Authors:
Categories: Mathematics
Type: BOOK - Published: 2012-01-09 - Publisher: ScholarlyEditions

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Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and c
Semismooth Newton Methods for Variational Inequalities and Constrained Optimization Problems in Function Spaces
Language: en
Pages: 322

Semismooth Newton Methods for Variational Inequalities and Constrained Optimization Problems in Function Spaces

Authors: Michael Ulbrich
Categories: Constrained optimization
Type: BOOK - Published: 2011-01-01 - Publisher: SIAM

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Semismooth Newton methods are a modern class of remarkably powerful and versatile algorithms for solving constrained optimization problems with partial differen