Derivative-Free and Blackbox Optimization (Springer Series in Operations Research and Financial Engineering)
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- Synopsis
- 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.
- Copyright:
- 2017
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783319689135
- Related ISBNs:
- 9783319689128
- Publisher:
- Springer International Publishing
- Date of Addition:
- 10/14/18
- Copyrighted By:
- Springer International Publishing, Cham
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
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