A Derivative-free Two Level Random Search Method for Unconstrained Optimization
Language: en
Pages: 126
Authors: Neculai Andrei
Categories: Mathematics
Type: BOOK - Published: 2021-03-31 - Publisher: Springer Nature

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The book is intended for graduate students and researchers in mathematics, computer science, and operational research. The book presents a new derivative-free o
Derivative-Free and Blackbox Optimization
Language: en
Pages: 307
Authors: Charles Audet
Categories: Mathematics
Type: BOOK - Published: 2017-12-02 - Publisher: Springer

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This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization. Th
Introduction to Derivative-Free Optimization
Language: en
Pages: 276
Authors: Andrew R. Conn
Categories: Mathematics
Type: BOOK - Published: 2009-04-16 - Publisher: SIAM

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The first contemporary comprehensive treatment of optimization without derivatives. This text explains how sampling and model techniques are used in derivative-
Modern Numerical Nonlinear Optimization
Language: en
Pages: 824
Authors: Neculai Andrei
Categories: Mathematics
Type: BOOK - Published: 2022-10-18 - Publisher: Springer Nature

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This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the mo
Implicit Filtering
Language: en
Pages: 171
Authors: C. T. Kelley
Categories: Mathematics
Type: BOOK - Published: 2011-09-29 - Publisher: SIAM

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A description of the implicit filtering algorithm, its convergence theory and a new MATLABĀ® implementation.