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Lagrange Multiplier Methods for Constrained Optimization and Variational Problems in Banach Spaces

Lagrange Multiplier Methods for Constrained Optimization and Variational Problems in Banach Spaces PDF Author: Daniel Steck
Publisher:
ISBN:
Category : Banach spaces
Languages : en
Pages :

Book Description


Lagrange Multiplier Methods for Constrained Optimization and Variational Problems in Banach Spaces

Lagrange Multiplier Methods for Constrained Optimization and Variational Problems in Banach Spaces PDF Author: Daniel Steck
Publisher:
ISBN:
Category : Banach spaces
Languages : en
Pages :

Book Description


Lagrange Multiplier Approach to Variational Problems and Applications

Lagrange Multiplier Approach to Variational Problems and Applications PDF Author: Kazufumi Ito
Publisher: SIAM
ISBN: 9780898718614
Category : Mathematics
Languages : en
Pages : 359

Book Description
Lagrange multiplier theory provides a tool for the analysis of a general class of nonlinear variational problems and is the basis for developing efficient and powerful iterative methods for solving these problems. This comprehensive monograph analyzes Lagrange multiplier theory and shows its impact on the development of numerical algorithms for problems posed in a function space setting. The authors develop and analyze efficient algorithms for constrained optimization and convex optimization problems based on the augumented Lagrangian concept and cover such topics as sensitivity analysis, convex optimization, second order methods, and shape sensitivity calculus. General theory is applied to challenging problems in optimal control of partial differential equations, image analysis, mechanical contact and friction problems, and American options for the Black-Scholes model.

Constrained Optimization and Lagrange Multiplier Methods

Constrained Optimization and Lagrange Multiplier Methods PDF Author: Dimitri P. Bertsekas
Publisher: Academic Press
ISBN: 148326047X
Category : Mathematics
Languages : en
Pages : 412

Book Description
Computer Science and Applied Mathematics: Constrained Optimization and Lagrange Multiplier Methods focuses on the advancements in the applications of the Lagrange multiplier methods for constrained minimization. The publication first offers information on the method of multipliers for equality constrained problems and the method of multipliers for inequality constrained and nondifferentiable optimization problems. Discussions focus on approximation procedures for nondifferentiable and ill-conditioned optimization problems; asymptotically exact minimization in the methods of multipliers; duality framework for the method of multipliers; and the quadratic penalty function method. The text then examines exact penalty methods, including nondifferentiable exact penalty functions; linearization algorithms based on nondifferentiable exact penalty functions; differentiable exact penalty functions; and local and global convergence of Lagrangian methods. The book ponders on the nonquadratic penalty functions of convex programming. Topics include large scale separable integer programming problems and the exponential method of multipliers; classes of penalty functions and corresponding methods of multipliers; and convergence analysis of multiplier methods. The text is a valuable reference for mathematicians and researchers interested in the Lagrange multiplier methods.

Nonlinear Analysis and Variational Problems

Nonlinear Analysis and Variational Problems PDF Author: Panos M. Pardalos
Publisher: Springer Science & Business Media
ISBN: 1441901582
Category : Business & Economics
Languages : en
Pages : 502

Book Description
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.

Lagrange Multiplier Approach to Variational Problems and Applications

Lagrange Multiplier Approach to Variational Problems and Applications PDF Author: Kazufumi Ito
Publisher: SIAM
ISBN: 0898716497
Category : Mathematics
Languages : en
Pages : 354

Book Description
Analyses Lagrange multiplier theory and demonstrates its impact on the development of numerical algorithms for variational problems in function spaces.

Practical Augmented Lagrangian Methods for Constrained Optimization

Practical Augmented Lagrangian Methods for Constrained Optimization PDF Author: Ernesto G. Birgin
Publisher: SIAM
ISBN: 1611973368
Category : Mathematics
Languages : en
Pages : 222

Book Description
This book focuses on Augmented Lagrangian techniques for solving practical constrained optimization problems. The authors: rigorously delineate mathematical convergence theory based on sequential optimality conditions and novel constraint qualifications; orient the book to practitioners by giving priority to results that provide insight on the practical behavior of algorithms and by providing geometrical and algorithmic interpretations of every mathematical result; and fully describe a freely available computational package for constrained optimization and illustrate its usefulness with applications.

Recent Developments in Optimization

Recent Developments in Optimization PDF Author: Roland Durier
Publisher: Springer Science & Business Media
ISBN: 3642468233
Category : Mathematics
Languages : en
Pages : 369

Book Description
The main objective of this volume is to provide a presentation and discussion of recent developments in optimization and related fields. Equal emphasis is given to theoretical and practical studies. All the papers in this volume contain original results except two of them which are survey contributions. They deal with a wide range of topics such as optimization and variational inequalities, sensitivity and stability analysis, control theory, convex and nonsmooth analysis, and numerical methods.

Optimization by Vector Space Methods

Optimization by Vector Space Methods PDF Author: David G. Luenberger
Publisher: John Wiley & Sons
ISBN: 9780471181170
Category : Technology & Engineering
Languages : en
Pages : 348

Book Description
Engineers must make decisions regarding the distribution of expensive resources in a manner that will be economically beneficial. This problem can be realistically formulated and logically analyzed with optimization theory. This book shows engineers how to use optimization theory to solve complex problems. Unifies the large field of optimization with a few geometric principles. Covers functional analysis with a minimum of mathematics. Contains problems that relate to the applications in the book.

Advances in Optimization

Advances in Optimization PDF Author: Werner Oettli
Publisher: Springer Science & Business Media
ISBN: 3642516823
Category : Business & Economics
Languages : en
Pages : 527

Book Description
This voluume contains actual contributions to the current research directions in Optimizatiton Theory as well as applications to economic problems and to problems in industrial engineering. Of particular interest are: convex- and Nonsmooth Analysis, Sensitivity Theory, Optimization techniques for nonsmooth and Variational problems, Control Theory and Vector optimization. The volume contains research andsurvey papers. The main benefit is given by a global suruvey of the state ofart of modern Optimization Theory and some typical applications.

Lagrange-type Functions in Constrained Non-Convex Optimization

Lagrange-type Functions in Constrained Non-Convex Optimization PDF Author: Alexander M. Rubinov
Publisher: Springer Science & Business Media
ISBN: 1441991727
Category : Mathematics
Languages : en
Pages : 297

Book Description
Lagrange and penalty function methods provide a powerful approach, both as a theoretical tool and a computational vehicle, for the study of constrained optimization problems. However, for a nonconvex constrained optimization problem, the classical Lagrange primal-dual method may fail to find a mini mum as a zero duality gap is not always guaranteed. A large penalty parameter is, in general, required for classical quadratic penalty functions in order that minima of penalty problems are a good approximation to those of the original constrained optimization problems. It is well-known that penaity functions with too large parameters cause an obstacle for numerical implementation. Thus the question arises how to generalize classical Lagrange and penalty functions, in order to obtain an appropriate scheme for reducing constrained optimiza tion problems to unconstrained ones that will be suitable for sufficiently broad classes of optimization problems from both the theoretical and computational viewpoints. Some approaches for such a scheme are studied in this book. One of them is as follows: an unconstrained problem is constructed, where the objective function is a convolution of the objective and constraint functions of the original problem. While a linear convolution leads to a classical Lagrange function, different kinds of nonlinear convolutions lead to interesting generalizations. We shall call functions that appear as a convolution of the objective function and the constraint functions, Lagrange-type functions.