Trust-Region Methods
Will be published approx. on 30. September 2000
Book
Hardback
978 pages
978-0-89871-460-9 (ISBN)
Description
This is the first comprehensive reference on trust-region methods, a class of numerical algorithms for the solution of nonlinear convex optimization methods. Its unified treatment covers both unconstrained and constrained problems and reviews a large part of the specialized literature on the subject. It also provides an up-to-date view of numerical optimization.
Written primarily for postgraduates and researchers, the book features an extensive commented bibliography, which contains more than 1000 references by over 750 authors. The book also contains several practical comments and an entire chapter devoted to software and implementation issues. Its many illustrations, including nearly 100 figures, balance the formal and intuitive treatment of the presented topics.
Written primarily for postgraduates and researchers, the book features an extensive commented bibliography, which contains more than 1000 references by over 750 authors. The book also contains several practical comments and an entire chapter devoted to software and implementation issues. Its many illustrations, including nearly 100 figures, balance the formal and intuitive treatment of the presented topics.
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Dimensions
Height: 261 mm
Width: 183 mm
Thickness: 50 mm
Weight
1880 gr
ISBN-13
978-0-89871-460-9 (9780898714609)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Preface
Chapter 1: Introduction
Part I: Preliminaries
Chapter 2: Basic Concepts
Chapter 3: Basic Analysis and Optimality Conditions
Chapter 4: Basic Linear Algebra
Chapter 5 Krylov Subspace Methods
Part II: Trust-Region Methods For Unconstrained Optimization
Chapter 6: Global Convergence of the Basic Algorithm
Chapter 7: The Trust-Region Subproblem
Chapter 8: Further Convergence Theory Issues
Chapter 9: Conditional Models
Chapter 10: Algorithmic Extensions
Chapter 11: Nonsmooth Problems
Part III: Trust-Region Methods For Constrained Optimization With Convex Constraints
Chapter 12: Projection Methods for Convex Constraints
Chapter 13: Barrier Methods for Inequality Constraints
Part IV: Trust-Region Methods For General Constrained Optimization and Systems of Nonlinear Equations
Chapter 14: Penalty-Function Methods
Chapter 15: Sequential Quadratic Programming Methods
Chapter 16: Nonlinear Equations and Nonlinear Fitting
Part V: Final Considerations
Chapter 17: Practicalities
Afterword
Appendix: A Summary of Assumptions
Annotated Bibliography
Subject and Notation Index
Author Index.
Chapter 1: Introduction
Part I: Preliminaries
Chapter 2: Basic Concepts
Chapter 3: Basic Analysis and Optimality Conditions
Chapter 4: Basic Linear Algebra
Chapter 5 Krylov Subspace Methods
Part II: Trust-Region Methods For Unconstrained Optimization
Chapter 6: Global Convergence of the Basic Algorithm
Chapter 7: The Trust-Region Subproblem
Chapter 8: Further Convergence Theory Issues
Chapter 9: Conditional Models
Chapter 10: Algorithmic Extensions
Chapter 11: Nonsmooth Problems
Part III: Trust-Region Methods For Constrained Optimization With Convex Constraints
Chapter 12: Projection Methods for Convex Constraints
Chapter 13: Barrier Methods for Inequality Constraints
Part IV: Trust-Region Methods For General Constrained Optimization and Systems of Nonlinear Equations
Chapter 14: Penalty-Function Methods
Chapter 15: Sequential Quadratic Programming Methods
Chapter 16: Nonlinear Equations and Nonlinear Fitting
Part V: Final Considerations
Chapter 17: Practicalities
Afterword
Appendix: A Summary of Assumptions
Annotated Bibliography
Subject and Notation Index
Author Index.