Introduction to Derivative-Free Optimization

丛 书 名：Mps-Siam Series on Optimization

作     者：Andrew R. Conn Katya Scheinberg Luís N. Vicente 

I S B N：(纸本) 9780898716689 

出 版 社：Cambridge University Press 

出 版 年：2009年

主 题 词：Engineering mathematics Industrial engineering Search theory Nonlinear theories Mathematical models Mathematical optimization 

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

馆 藏 号：201734258...

摘      要：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.