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Springer Series in Operations Research and Financial Engineering

Derivative-Free and Blackbox Optimization

Authors: Audet, Charles, Hare, Warren

  • Flexible usage suitable for undergraduate, graduate, mathematics, computer science, engineering, or mixed classes
  • 15 end-of-chapter projects are provided, allowing advanced exploration of desired topics
  • Includes numerous exercises throughout to test knowledge and advance understanding
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eBook $69.99
price for Mexico (gross)
  • ISBN 978-3-319-68913-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.99
price for Mexico
  • ISBN 978-3-319-68912-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

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.

About the authors

Dr. Charles Audet is a Professor of Mathematics at the École Polytechnique de Montréal. His research interests include the analysis and development of algorithms for blackbox nonsmooth optimization, and structured global optimization. He obtained a Ph.D. degree in applied mathematics from the École Polytechnique de Montréal, and worked as a post-doc at Rice University in Houston, Texas.

Dr. Warren Hare received his Ph.D. in Mathematical Optimization from Simon Fraser University.  He complete postdoctoral research at IMPA (Brazil) and McMaster (Canada), before joining the University of British Columbia (Canada).  

Table of contents (14 chapters)

  • Introduction: Tools and Challenges in Derivative-Free and Blackbox Optimization

    Audet, Charles (et al.)

    Pages 3-14

  • Mathematical Background

    Audet, Charles (et al.)

    Pages 15-31

  • The Beginnings of DFO Algorithms

    Audet, Charles (et al.)

    Pages 33-54

  • Genetic Algorithms

    Audet, Charles (et al.)

    Pages 57-73

  • Nelder-Mead

    Audet, Charles (et al.)

    Pages 75-91

Buy this book

eBook $69.99
price for Mexico (gross)
  • ISBN 978-3-319-68913-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.99
price for Mexico
  • ISBN 978-3-319-68912-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Derivative-Free and Blackbox Optimization
Authors
Series Title
Springer Series in Operations Research and Financial Engineering
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-68913-5
DOI
10.1007/978-3-319-68913-5
Hardcover ISBN
978-3-319-68912-8
Series ISSN
1431-8598
Edition Number
1
Number of Pages
XVIII, 302
Number of Illustrations and Tables
38 b/w illustrations
Topics