Introduction to Nonsmooth Optimization

Theory, Practice and Software

  • Adil Bagirov
  • Napsu Karmitsa
  • Marko M. Mäkelä

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Nonsmooth Analysis and Optimization

    1. Front Matter
      Pages 1-2
    2. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 3-9
    3. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 11-60
    4. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 61-116
    5. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 117-137
    6. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 139-168
    7. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 169-197
    8. Back Matter
      Pages 199-200
  3. Nonsmooth Problems

    1. Front Matter
      Pages 201-202
    2. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 203-240
    3. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 241-245
    4. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 247-285
    5. Back Matter
      Pages 287-291
  4. Nonsmooth Optimization Methods

    1. Front Matter
      Pages 293-294
    2. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 295-297
    3. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 299-303
    4. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 305-310
    5. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 311-312
    6. Adil Bagirov, Napsu Karmitsa, Marko M. Mäkelä
      Pages 313-325

About this book

Introduction

This book is the first easy-to-read text on nonsmooth optimization (NSO, not necessarily differentiable optimization). Solving these kinds of problems plays a critical role in many industrial applications and real-world modeling systems, for example in the context of image denoising, optimal control, neural network training, data mining, economics, and computational chemistry and physics. The book covers both the theory and the numerical methods used in NSO, and provides an overview of different problems arising in the field. It is organized into three parts:

1.convex and nonconvex analysis and the theory of NSO;

2.test problems and practical applications;

3.a guide to NSO software.

The book is ideal for anyone teaching or attending NSO courses. As an accessible introduction to the field, it is also well suited as an independent learning guide for practitioners already familiar with the basics of optimization.

Keywords

Bundle methods Nondifferentiable optimization Nonsmooth analysis Subgradient methods Test problems

Authors and affiliations

  • Adil Bagirov
    • 1
  • Napsu Karmitsa
    • 2
  • Marko M. Mäkelä
    • 3
  1. 1.Centre for Informatics and Applied OptimizationUniversity of Ballarat School of Information Technology & MatBallaratAustralia
  2. 2.University of Turku Department of Mathematics and StatisticsTurkuFinland
  3. 3.Department of Mathematics and StatisticsUniversity of TurkuTurkuFinland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-08114-4
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Business and Economics
  • Print ISBN 978-3-319-08113-7
  • Online ISBN 978-3-319-08114-4