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Conn A. Introduction to Derivative-Free Optimization 2009

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Conn A. Introduction to Derivative-Free Optimization 2009

Conn A. Introduction to Derivative-Free Optimization 2009

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Info:
  • Title: Introduction to Derivative-Free Optimization
  • Pages: 289
  • Author: Andrew R. Conn
  • Language: English
  • Year: 2009
  • Subjects:
  • Category: Linear Programming, Statistics, Probability & Statistics
  • Publisher: ‎ Society for Industrial and Applied Mathematics
  • ISBN: ‎ 978-0898716689

Description:
The absence of derivatives, often combined with the presence of noise or lack of smoothness, is a major challenge for optimization. This book explains how sampling and model techniques are used in derivative-free methods and how these methods are designed to efficiently and rigorously solve optimization problems. Although readily accessible to readers with a modest background in computational mathematics, it is also intended to be of interest to researchers in the field. Introduction to Derivative-Free Optimization is the first contemporary comprehensive treatment of optimization without derivatives. This book covers most of the relevant classes of algorithms from direct search to model-based approaches. It contains a comprehensive description of the sampling and modeling tools needed for derivative-free optimization; these tools allow the reader to better analyze the convergent properties of the algorithms and identify their differences and similarities.

Files:
Conn A. Introduction to Derivative Free Optimization 2009.pdf (1.66 MB)

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