Linear and Nonlinear Conjugate Gradient-related Methods

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Publisher : SIAM
ISBN 13 : 9780898713763
Total Pages : 186 pages
Book Rating : 4.65/5 ( download)

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Book Synopsis Linear and Nonlinear Conjugate Gradient-related Methods by : Loyce M. Adams

Download or read book Linear and Nonlinear Conjugate Gradient-related Methods written by Loyce M. Adams and published by SIAM. This book was released on 1996-01-01 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the AMS-IMS-SIAM Summer Research Conference held at the University of Washington, July 1995.

Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

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Publisher : Springer Nature
ISBN 13 : 3030429504
Total Pages : 515 pages
Book Rating : 4.08/5 ( download)

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Book Synopsis Nonlinear Conjugate Gradient Methods for Unconstrained Optimization by : Neculai Andrei

Download or read book Nonlinear Conjugate Gradient Methods for Unconstrained Optimization written by Neculai Andrei and published by Springer Nature. This book was released on 2020-06-23 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. This is the first book to detail conjugate gradient methods, showing their properties and convergence characteristics as well as their performance in solving large-scale unconstrained optimization problems and applications. Comparisons to the limited-memory and truncated Newton methods are also discussed. Topics studied in detail include: linear conjugate gradient methods, standard conjugate gradient methods, acceleration of conjugate gradient methods, hybrid, modifications of the standard scheme, memoryless BFGS preconditioned, and three-term. Other conjugate gradient methods with clustering the eigenvalues or with the minimization of the condition number of the iteration matrix, are also treated. For each method, the convergence analysis, the computational performances and the comparisons versus other conjugate gradient methods are given. The theory behind the conjugate gradient algorithms presented as a methodology is developed with a clear, rigorous, and friendly exposition; the reader will gain an understanding of their properties and their convergence and will learn to develop and prove the convergence of his/her own methods. Numerous numerical studies are supplied with comparisons and comments on the behavior of conjugate gradient algorithms for solving a collection of 800 unconstrained optimization problems of different structures and complexities with the number of variables in the range [1000,10000]. The book is addressed to all those interested in developing and using new advanced techniques for solving unconstrained optimization complex problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master students in mathematical programming, will find plenty of information and practical applications for solving large-scale unconstrained optimization problems and applications by conjugate gradient methods.

Conjugate Gradient Algorithms and Finite Element Methods

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Publisher : Springer Science & Business Media
ISBN 13 : 3642185606
Total Pages : 405 pages
Book Rating : 4.01/5 ( download)

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Book Synopsis Conjugate Gradient Algorithms and Finite Element Methods by : Michal Krizek

Download or read book Conjugate Gradient Algorithms and Finite Element Methods written by Michal Krizek and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: The position taken in this collection of pedagogically written essays is that conjugate gradient algorithms and finite element methods complement each other extremely well. Via their combinations practitioners have been able to solve complicated, direct and inverse, multidemensional problems modeled by ordinary or partial differential equations and inequalities, not necessarily linear, optimal control and optimal design being part of these problems. The aim of this book is to present both methods in the context of complicated problems modeled by linear and nonlinear partial differential equations, to provide an in-depth discussion on their implementation aspects. The authors show that conjugate gradient methods and finite element methods apply to the solution of real-life problems. They address graduate students as well as experts in scientific computing.

Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

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Publisher : Springer
ISBN 13 : 9783030429492
Total Pages : 486 pages
Book Rating : 4.90/5 ( download)

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Book Synopsis Nonlinear Conjugate Gradient Methods for Unconstrained Optimization by : Neculai Andrei

Download or read book Nonlinear Conjugate Gradient Methods for Unconstrained Optimization written by Neculai Andrei and published by Springer. This book was released on 2020-06-29 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. This is the first book to detail conjugate gradient methods, showing their properties and convergence characteristics as well as their performance in solving large-scale unconstrained optimization problems and applications. Comparisons to the limited-memory and truncated Newton methods are also discussed. Topics studied in detail include: linear conjugate gradient methods, standard conjugate gradient methods, acceleration of conjugate gradient methods, hybrid, modifications of the standard scheme, memoryless BFGS preconditioned, and three-term. Other conjugate gradient methods with clustering the eigenvalues or with the minimization of the condition number of the iteration matrix, are also treated. For each method, the convergence analysis, the computational performances and the comparisons versus other conjugate gradient methods are given. The theory behind the conjugate gradient algorithms presented as a methodology is developed with a clear, rigorous, and friendly exposition; the reader will gain an understanding of their properties and their convergence and will learn to develop and prove the convergence of his/her own methods. Numerous numerical studies are supplied with comparisons and comments on the behavior of conjugate gradient algorithms for solving a collection of 800 unconstrained optimization problems of different structures and complexities with the number of variables in the range [1000,10000]. The book is addressed to all those interested in developing and using new advanced techniques for solving unconstrained optimization complex problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master students in mathematical programming, will find plenty of information and practical applications for solving large-scale unconstrained optimization problems and applications by conjugate gradient methods.

Conjugate Gradient Algorithms in Nonconvex Optimization

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 354085634X
Total Pages : 493 pages
Book Rating : 4.44/5 ( download)

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Book Synopsis Conjugate Gradient Algorithms in Nonconvex Optimization by : Radoslaw Pytlak

Download or read book Conjugate Gradient Algorithms in Nonconvex Optimization written by Radoslaw Pytlak and published by Springer Science & Business Media. This book was released on 2008-11-18 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book details algorithms for large-scale unconstrained and bound constrained optimization. It shows optimization techniques from a conjugate gradient algorithm perspective as well as methods of shortest residuals, which have been developed by the author.

A Multigrid Tutorial

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Publisher : SIAM
ISBN 13 : 9780898714623
Total Pages : 318 pages
Book Rating : 4.21/5 ( download)

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Book Synopsis A Multigrid Tutorial by : William L. Briggs

Download or read book A Multigrid Tutorial written by William L. Briggs and published by SIAM. This book was released on 2000-07-01 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- Numerical Analysis.

Preconditioned Conjugate-Gradient 2 (PCG2), a Computer Program for Solving Ground-water Flow Equations

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Publisher :
ISBN 13 :
Total Pages : 54 pages
Book Rating : 4.92/5 ( download)

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Book Synopsis Preconditioned Conjugate-Gradient 2 (PCG2), a Computer Program for Solving Ground-water Flow Equations by : Mary Catherine Hill

Download or read book Preconditioned Conjugate-Gradient 2 (PCG2), a Computer Program for Solving Ground-water Flow Equations written by Mary Catherine Hill and published by . This book was released on 1990 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods

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Publisher : Springer Science & Business Media
ISBN 13 : 9780792353201
Total Pages : 468 pages
Book Rating : 4.0X/5 ( download)

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Book Synopsis Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods by : Masao Fukushima

Download or read book Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods written by Masao Fukushima and published by Springer Science & Business Media. This book was released on 1999 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Iterative Methods for Sparse Linear Systems

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Publisher : SIAM
ISBN 13 : 0898715342
Total Pages : 537 pages
Book Rating : 4.47/5 ( download)

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Book Synopsis Iterative Methods for Sparse Linear Systems by : Yousef Saad

Download or read book Iterative Methods for Sparse Linear Systems written by Yousef Saad and published by SIAM. This book was released on 2003-04-01 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- General.

The Conjugate Gradient Method for Linear and Nonlinear Operator Equations

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Publisher :
ISBN 13 :
Total Pages : 198 pages
Book Rating : 4.82/5 ( download)

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Book Synopsis The Conjugate Gradient Method for Linear and Nonlinear Operator Equations by : James W. Daniel

Download or read book The Conjugate Gradient Method for Linear and Nonlinear Operator Equations written by James W. Daniel and published by . This book was released on 1965 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: