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商品詳細
Derivative-Free and Blackbox Optimization. 1st ed. 2017.
・ISBN 978-3-319-68912-8 hard EUR 89.99
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| 著者・編者 | Audet, Charles / Hare, Warren, |
|---|---|
| シリーズ | Springer Series in Operations Research and Financial Engineering |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2017 |
| ページ数 | 302 pp. |
| 言語 | ENG |
| ニュース番号 | ＜M25-4674＞ |
解説
This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization.
The book is split into 5 parts and is designed to be modular; any individual part depends only on the material in Part I. Part I of the book discusses what is meant by Derivative-Free and Blackbox Optimization, provides background material, and early basics while Part II focuses on heuristic methods (Genetic Algorithms and Nelder-Mead). Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region). Part V discusses dealing with constraints, using surrogates, and bi-objective optimization.
End of chapter exercises are included throughout as well as 15 end of chapter projects and over 40 figures. Benchmarking techniques are also presented in the appendix.