Newton-Type Methods for Optimization and Variational Problems
Newton-Type Methods for Optimization and Variational Problems

Author: Alexey F. Izmailov

Publisher: Springer

Published: 2014-07-08

Total Pages: 587

ISBN-13: 3319042475

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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 variational problems. A central focus is the relationship between the basic Newton scheme for a given problem and algorithms that also enjoy fast local convergence. The authors develop general perturbed Newtonian frameworks that preserve fast convergence and consider specific algorithms as particular cases within those frameworks, i.e., as perturbations of the associated basic Newton iterations. This approach yields a set of tools for the unified treatment of various algorithms, including some not of the Newton type per se. Among the new subjects addressed is the class of degenerate problems. In particular, the phenomenon of attraction of Newton iterates to critical Lagrange multipliers and its consequences as well as stabilized Newton methods for variational problems and stabilized sequential quadratic programming for optimization. This volume will be useful to researchers and graduate students in the fields of optimization and variational analysis.

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

Author: Michael Ulbrich

Publisher: SIAM

Published: 2011-07-28

Total Pages: 315

ISBN-13: 1611970687

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A comprehensive treatment of semismooth Newton methods in function spaces: from their foundations to recent progress in the field. This book is appropriate for researchers and practitioners in PDE-constrained optimization, nonlinear optimization and numerical analysis, as well as engineers interested in the current theory and methods for solving variational inequalities.

Numerical Optimization with Computational Errors
Numerical Optimization with Computational Errors

Author: Alexander J. Zaslavski

Publisher: Springer

Published: 2016-04-22

Total Pages: 308

ISBN-13: 3319309218

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This book studies the approximate solutions of optimization problems in the presence of computational errors. A number of results are presented on the convergence behavior of algorithms in a Hilbert space; these algorithms are examined taking into account computational errors. The author illustrates that algorithms generate a good approximate solution, if computational errors are bounded from above by a small positive constant. Known computational errors are examined with the aim of determining an approximate solution. Researchers and students interested in the optimization theory and its applications will find this book instructive and informative. This monograph contains 16 chapters; including a chapters devoted to the subgradient projection algorithm, the mirror descent algorithm, gradient projection algorithm, the Weiszfelds method, constrained convex minimization problems, the convergence of a proximal point method in a Hilbert space, the continuous subgradient method, penalty methods and Newton’s method.

Convergence and Applications of Newton-type Iterations
Convergence and Applications of Newton-type Iterations

Author: Ioannis K. Argyros

Publisher: Springer Science & Business Media

Published: 2008-06-12

Total Pages: 513

ISBN-13: 0387727434

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This monograph is devoted to a comprehensive treatment of iterative methods for solving nonlinear equations with particular emphasis on semi-local convergence analysis. Theoretical results are applied to engineering, dynamic economic systems, input-output systems, nonlinear and linear differential equations, and optimization problems. Accompanied by many exercises, some with solutions, the book may be used as a supplementary text in the classroom for an advanced course on numerical functional analysis.

Lectures on Variational Analysis
Lectures on Variational Analysis

Author: Asen L. Dontchev

Publisher: Springer Nature

Published: 2022-02-04

Total Pages: 223

ISBN-13: 3030799115

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This book presents an introduction to variational analysis, a field which unifies theories and techniques developed in calculus of variations, optimization, and control, and covers convex analysis, nonsmooth analysis, and set-valued analysis. It focuses on problems with constraints, the analysis of which involves set-valued mappings and functions that are not differentiable. Applications of variational analysis are interdisciplinary, ranging from financial planning to steering a flying object. The book is addressed to graduate students, researchers, and practitioners in mathematical sciences, engineering, economics, and finance. A typical reader of the book should be familiar with multivariable calculus and linear algebra. Some basic knowledge in optimization, control, and elementary functional analysis is desirable, but all necessary background material is included in the book.

Complementarity and Variational Problems
Complementarity and Variational Problems

Author: Michael C. Ferris

Publisher: SIAM

Published: 1997-01-01

Total Pages: 494

ISBN-13: 9780898713916

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After more than three decades of research, the subject of complementarity problems and its numerous extensions has become a well-established and fruitful discipline within mathematical programming and applied mathematics. Sources of these problems are diverse and span numerous areas in engineering, economics, and the sciences. Includes refereed articles.

Nonlinear Analysis and Variational Problems
Nonlinear Analysis and Variational Problems

Author: Panos M. Pardalos

Publisher: Springer Science & Business Media

Published: 2009-10-20

Total Pages: 502

ISBN-13: 1441901582

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The chapters in this volume, written by international experts from different fields of mathematics, are devoted to honoring George Isac, a renowned mathematician. These contributions focus on recent developments in complementarity theory, variational principles, stability theory of functional equations, nonsmooth optimization, and several other important topics at the forefront of nonlinear analysis and optimization.

Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods
Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods

Author: Masao Fukushima

Publisher: Springer Science & Business Media

Published: 1999

Total Pages: 468

ISBN-13: 9780792353201

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The concept of `reformulation' has long played an important role in mathematical programming. A classical example is the penalization technique in constrained optimization. More recent trends consist of reformulation of various mathematical programming problems, including variational inequalities and complementarity problems, into equivalent systems of possibly nonsmooth, piecewise smooth or semismooth nonlinear equations, or equivalent unconstrained optimization problems that are usually differentiable, but in general not twice differentiable. The book is a collection of peer-reviewed papers that cover such diverse areas as linear and nonlinear complementarity problems, variational inequality problems, nonsmooth equations and nonsmooth optimization problems, economic and network equilibrium problems, semidefinite programming problems, maximal monotone operator problems, and mathematical programs with equilibrium constraints. The reader will be convinced that the concept of `reformulation' provides extremely useful tools for advancing the study of mathematical programming from both theoretical and practical aspects. Audience: This book is intended for students and researchers in optimization, mathematical programming, and operations research.