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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.

Parametre knihy

Zaradenie knihy Knihy po anglicky Mathematics & science Mathematics Optimization

• Celý názov: Introduction to Derivative-Free Optimization
• Autor: Andrew R. ConnKatya ScheinbergLuís N. Vicente
• Jazyk: Angličtina
• Väzba: Brožovaná
• Počet strán: 289
• EAN: 9780898716689
• ISBN: 0898716683
• ID: 02050226
• Nakladateľ: Society for Industrial & Applied Mathematics,U.S.
• Hmotnosť: 53 g
• Rozmery: 256 × 182 × 18 mm
• Dátum vydania: 30. January 2008

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