Iterative methods for optimization:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia, Pa.
Society for Industrial and Applied Mathematics
1999
|
| Schriftenreihe: | Frontiers in applied mathematics
18 |
| Schlagworte: | |
| Online-Zugang: | TUM01 UBW01 UBY01 UER01 Volltext |
| Beschreibung: | Mode of access: World Wide Web. - System requirements: Adobe Acrobat Reader Includes bibliographical references (p. 161-176) and index Preface -- How to get the software -- Part I. Optimization of smooth functions. Chapter 1. Basic concepts; Chapter 2. Local convergence of Newton's method; Chapter 3. Global convergence; Chapter 4. The BFGS method; Chapter 5. Simple bound constraints -- Part II. Optimization of noisy functions. Chapter 6. Basic concepts and goals; Chapter 7. Implicit filtering; Chapter 8. Direct search algorithms -- Bibliography -- Index This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages |
| Beschreibung: | 1 Online-Ressource (xv, 180 Seiten) |
| ISBN: | 0898714338 9780898714333 |
| DOI: | 10.1137/1.9781611970920 |
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| 500 | |a Includes bibliographical references (p. 161-176) and index | ||
| 500 | |a Preface -- How to get the software -- Part I. Optimization of smooth functions. Chapter 1. Basic concepts; Chapter 2. Local convergence of Newton's method; Chapter 3. Global convergence; Chapter 4. The BFGS method; Chapter 5. Simple bound constraints -- Part II. Optimization of noisy functions. Chapter 6. Basic concepts and goals; Chapter 7. Implicit filtering; Chapter 8. Direct search algorithms -- Bibliography -- Index | ||
| 500 | |a This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages | ||
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Datensatz im Suchindex
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| id | DE-604.BV039747375 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T00:10:18Z |
| institution | BVB |
| isbn | 0898714338 9780898714333 |
| language | English |
| lccn | 99011141 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024594906 |
| oclc_num | 873886309 |
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| physical | 1 Online-Ressource (xv, 180 Seiten) |
| psigel | ZDB-72-SIA |
| publishDate | 1999 |
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| publishDateSort | 1999 |
| publisher | Society for Industrial and Applied Mathematics |
| record_format | marc |
| series | Frontiers in applied mathematics |
| series2 | Frontiers in applied mathematics |
| spelling | Kelley, C. T. (DE-588)114209642 aut Iterative methods for optimization C.T. Kelley Philadelphia, Pa. Society for Industrial and Applied Mathematics 1999 1 Online-Ressource (xv, 180 Seiten) txt rdacontent c rdamedia cr rdacarrier Frontiers in applied mathematics 18 Mode of access: World Wide Web. - System requirements: Adobe Acrobat Reader Includes bibliographical references (p. 161-176) and index Preface -- How to get the software -- Part I. Optimization of smooth functions. Chapter 1. Basic concepts; Chapter 2. Local convergence of Newton's method; Chapter 3. Global convergence; Chapter 4. The BFGS method; Chapter 5. Simple bound constraints -- Part II. Optimization of noisy functions. Chapter 6. Basic concepts and goals; Chapter 7. Implicit filtering; Chapter 8. Direct search algorithms -- Bibliography -- Index This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages Mathematical optimization Iterative methods (Mathematics) Optimierung (DE-588)4043664-0 gnd rswk-swf Iteration (DE-588)4123457-1 gnd rswk-swf Optimierung (DE-588)4043664-0 s Iteration (DE-588)4123457-1 s DE-604 Erscheint auch als Druck-Ausgabe, Paperback 0898714338 Erscheint auch als Druck-Ausgabe, Paperback 9780898714333 Frontiers in applied mathematics 18 (DE-604)BV047220606 18 https://doi.org/10.1137/1.9781611970920 Verlag Volltext |
| spellingShingle | Kelley, C. T. Iterative methods for optimization Frontiers in applied mathematics Mathematical optimization Iterative methods (Mathematics) Optimierung (DE-588)4043664-0 gnd Iteration (DE-588)4123457-1 gnd |
| subject_GND | (DE-588)4043664-0 (DE-588)4123457-1 |
| title | Iterative methods for optimization |
| title_auth | Iterative methods for optimization |
| title_exact_search | Iterative methods for optimization |
| title_full | Iterative methods for optimization C.T. Kelley |
| title_fullStr | Iterative methods for optimization C.T. Kelley |
| title_full_unstemmed | Iterative methods for optimization C.T. Kelley |
| title_short | Iterative methods for optimization |
| title_sort | iterative methods for optimization |
| topic | Mathematical optimization Iterative methods (Mathematics) Optimierung (DE-588)4043664-0 gnd Iteration (DE-588)4123457-1 gnd |
| topic_facet | Mathematical optimization Iterative methods (Mathematics) Optimierung Iteration |
| url | https://doi.org/10.1137/1.9781611970920 |
| volume_link | (DE-604)BV047220606 |
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