Derivative-Free and Blackbox Optimization

  • Charles Audet
  • Warren Hare

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Introduction and Background Material

    1. Front Matter
      Pages 1-1
    2. Charles Audet, Warren Hare
      Pages 15-31
    3. Charles Audet, Warren Hare
      Pages 33-54
  3. Popular Heuristic Methods

    1. Front Matter
      Pages 55-55
    2. Charles Audet, Warren Hare
      Pages 57-73
    3. Charles Audet, Warren Hare
      Pages 75-91
  4. Direct Search Methods

    1. Front Matter
      Pages 93-93
    2. Charles Audet, Warren Hare
      Pages 95-114
    3. Charles Audet, Warren Hare
      Pages 115-134
    4. Charles Audet, Warren Hare
      Pages 135-156
  5. Model-Based Methods

    1. Front Matter
      Pages 157-157
    2. Charles Audet, Warren Hare
      Pages 159-181
    3. Charles Audet, Warren Hare
      Pages 183-200
    4. Charles Audet, Warren Hare
      Pages 201-218
  6. Extensions and Refinements

    1. Front Matter
      Pages 219-219
    2. Charles Audet, Warren Hare
      Pages 221-234
    3. Charles Audet, Warren Hare
      Pages 235-246
    4. Charles Audet, Warren Hare
      Pages 247-262

About this book

Introduction

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.

Keywords

Derivative-Free Optimization Blackbox Optimization Heuristic Methods Direct Search Methods Mesh Adaptive Direct Search Model-based Methods Model-based Trust-region Nonsmooth Constraints Surrogate Models Optimization Benchmarking

Authors and affiliations

  • Charles Audet
    • 1
  • Warren Hare
    • 2
  1. 1.Dépt. Mathématiques et Génie IndustrielEcole Polytechnique de MontréalMontréalCanada
  2. 2.Department of MathematicsUniversity of British ColumbiaKelownaCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-68913-5
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-68912-8
  • Online ISBN 978-3-319-68913-5
  • Series Print ISSN 1431-8598
  • Series Online ISSN 2197-1773
  • About this book
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