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Derivative-free and blackbox optimization

✍ Scribed by Audet, Charles; Hare, Warren


Publisher
Springer International Publishing : Imprint : Springer
Year
2017
Tongue
English
Leaves
307
Series
Springer Series in Operations Research and Financial Engineering
Category
Library

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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 Β 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). Β Read more...

✦ Table of Contents


Content: Part I: Introduction and Background Material --
Introduction: Tools and Challenges --
Mathematical Background --
The Beginnings of DFO Algorithms --
Part I: Some Remarks on DFO --
Part II: Popular Heuristic Methods --
Genetic Algorithms --
Nelder-Mead --
Part II: Further Remarks on Heuristics --
Part III: Direct Search Methods --
Positive bases and Nonsmooth Optimization --
Generalized Pattern Search --
Mesh Adaptive Direct Search --
Part III: Further Remarks on Direct Search Methods --
Part IV: Model-based Methods --
Model-based Descent --
Model-based Trust Region --
Part IV: Further Remarks on Model-based Methods --
Part V: Extensions and Refinements --
Variables and Constraints --
Optimization Using Surrogates and Models --
Biobjective Optimization --
Part V: Final Remarks on DFO/BBO --
Part VI: Appendix: Comparing Optimization Methods --
Solutions to Selected Exercises.

✦ Subjects


Mathematics.;Numerical analysis.;Mathematical optimization.;Optimization.;Numerical Analysis.


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