Información General

• Autores: Jan A. Snyman
• Editores: New York : Springer, 2005
• Año de publicación: 2005
• País: Estados Unidos
• Idioma: inglés
• ISBN: 978-0-387-24348-1, 978-0-387-24349-8
• Texto completo no disponible (Saber más ...)

Resumen

• This book presents basic optimization principles and gradient-based algorithms to a general audience in a brief and easy-to-read form, without neglecting rigor. The work should enable professionals to apply optimization theory and algorithms to their own particular practical fields of interest, be it engineering, physics, chemistry, or business economics. Most importantly, for the first time in a relatively brief and introductory work, due attention is paid to the difficulties – such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima – that often unnecessarily inhibit the use of gradient-based methods. In a separate chapter on new gradient-based methods developed by the author and his coworkers, it is shown how these difficulties may be overcome without losing the desirable features of classical gradient-based methods.

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Índice

• Preface
  Table of Notation
  Chapter 1. Introduction
  Chapter 2. Line Search Descent Methods for Unconstrained Minimization
  Chapter 3. Standard Methods for Constrained Optimization
  Chapter 4. New Gradient-Based Trajectory and Approximation Methods
  Chapter 5. Example Problems
  Chapter 6. Some Theorems
  Chapter 7. The Simplex Method for Linear Programming Problems
  Bibliography
  Index