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Derivative-free and Blackbox Optimization by Charles Audet, Warren Hare is a nonfiction available to read on EtoBox.

What is Derivative-free and Blackbox Optimization about?

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. Read more... Abstract: 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). Read more...

Who reads Derivative-free and Blackbox Optimization?

Author

Charles Audet, Warren Hare

Publisher

Springer International Publishing : Imprint : Springer

Published

2017

Language

EN

ISBN

9783319689135

Category

nonfiction

Subjects

Mathematics, Science, Stem

Updated

2026-03-24