Advertisement

© 2008

Nonlinear Optimization with Engineering Applications

  • A sound theoretical introduction to optimization but mainly placing a practical emphasis on understanding algorithms and how to use them

Textbook

Part of the Springer Optimization and Its Applications book series (SOIA, volume 19)

Table of contents

  1. Front Matter
    Pages 1-15
  2. Michael Bartholomew–Biggs
    Pages 1-10
  3. Michael Bartholomew–Biggs
    Pages 1-22
  4. Michael Bartholomew–Biggs
    Pages 1-8
  5. Michael Bartholomew–Biggs
    Pages 1-12
  6. Michael Bartholomew–Biggs
    Pages 1-10
  7. Michael Bartholomew–Biggs
    Pages 1-12
  8. Michael Bartholomew–Biggs
    Pages 1-8
  9. Michael Bartholomew–Biggs
    Pages 1-8
  10. Michael Bartholomew–Biggs
    Pages 1-16
  11. Michael Bartholomew–Biggs
    Pages 1-12
  12. Michael Bartholomew–Biggs
    Pages 1-12
  13. Michael Bartholomew–Biggs
    Pages 1-2
  14. Michael Bartholomew–Biggs
    Pages 1-8
  15. Michael Bartholomew–Biggs
    Pages 1-6
  16. Michael Bartholomew–Biggs
    Pages 1-8
  17. Michael Bartholomew–Biggs
    Pages 1-14
  18. Michael Bartholomew–Biggs
    Pages 1-14
  19. Michael Bartholomew–Biggs
    Pages 1-14
  20. Michael Bartholomew–Biggs
    Pages 1-14

About this book

Introduction

This textbook examines a broad range of problems in science and engineering, describing key numerical methods applied to real life. The case studies presented are in such areas as data fitting, vehicle route planning and optimal control, scheduling and resource allocation, sensitivity calculations and worst-case analysis.

Among the main topics covered:

* one-variable optimization — optimality conditions, direct search and gradient

* unconstrained optimization in n variables — solution methods including Nelder and Mead simplex, steepest descent, Newton, Gauss–Newton, and quasi-Newton techniques, trust regions and conjugate gradients

* constrained optimization in n variables — solution methods including reduced-gradients, penalty and barrier methods, sequential quadratic programming, and interior point techniques

* an introduction to global optimization

* an introduction to automatic differentiation

Chapters are self-contained with exercises provided at the end of most sections. Nonlinear Optimization with Engineering Applications is ideal for self-study and classroom use in engineering courses at the senior undergraduate or graduate level. The book will also appeal to postdocs and advanced researchers interested in the development and use of optimization algorithms.

Also by the author: Nonlinear Optimization with Financial Applications,
ISBN: 978-1-4020-8110-1, (c)2005, Springer.

Keywords

algorithms global optimization linear optimization nonlinear optimization optimization quadratic programming scheduling

Authors and affiliations

  1. 1.Dept. of MathematicsUniversity of HertfordshireHatfieldUnited Kingdom

Bibliographic information

Industry Sectors
Electronics
Engineering
Finance, Business & Banking
Law

Reviews

From the reviews:

"This book gives on 280 pages a broad overview of nonlinear optimization. … The presented optimization approaches are compared with each other by means of several examples with up to 200 variables. … the introduction of the different techniques is written in a very comprehensible way. … each section contains exercises to verify and deepen the understanding of the material." (Andrea Walther, Zentralblatt MATH, Vol. 1167, 2009)