Conn A Introduction to Derivative-Free Optimization 2009
Date: 8 March 2023 | Posted by: BeMyLove
Conn A Introduction to Derivative-Free Optimization 2009 | 1.66 MB
English | 289 Pages
Title: Introduction to Derivative-Free Optimization
Author: Andrew R. Conn
Year: 2009
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.
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https://rapidgator.net/file/43ea9ac402d9080e6c362ba846831dcb/Conn_A._Introduction_to_Derivative-Free_Optimization_2009.rar
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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.
DOWNLOAD:
https://rapidgator.net/file/43ea9ac402d9080e6c362ba846831dcb/Conn_A._Introduction_to_Derivative-Free_Optimization_2009.rar
https://uploadgig.com/file/download/448f4d77b0faBdF8/Conn_A._Introduction_to_Derivative-Free_Optimization_2009.rar
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