Stochastic Global Optimization

Author:   Anatoly Zhigljavsky ,  Antanasz Zilinskas ,  Rainald Maass
Publisher:   Springer
ISBN:  

9780387520506


Pages:   276
Publication Date:   12 August 2008
Format:   Undefined
Availability:   Out of stock   Availability explained


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Stochastic Global Optimization


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Overview

This book examines the main methodological and theoretical developments in stochastic global optimization. It is designed to inspire readers to explore various stochastic methods of global optimization by clearly explaining the main methodological principles and features of the methods. Among the book's features is a comprehensive study of probabilistic and statistical models underlying the stochastic optimization algorithms.

Full Product Details

Author:   Anatoly Zhigljavsky ,  Antanasz Zilinskas ,  Rainald Maass
Publisher:   Springer
Imprint:   Springer
Dimensions:   Width: 23.40cm , Height: 1.50cm , Length: 15.60cm
Weight:   0.390kg
ISBN:  

9780387520506


ISBN 10:   0387520503
Pages:   276
Publication Date:   12 August 2008
Audience:   General/trade ,  General
Format:   Undefined
Publisher's Status:   Unknown
Availability:   Out of stock   Availability explained

Language:   English & German

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<p>From the reviews: <p> This excellent book is written for researchers interested in global optimization. the approach of carrying through from basic ideas to the most recent techniques will make this a valuable resource for the initiated. Gathering together contemporary methods and developments in stochastic global optimization, this text presents four chapters. (Tom Schulte, MathDL, February, 2008)<p> For global optimization, based on former monographs and articles of the authors on (global) random search, in this book global random search methods and stochastic models for the objective function are presented. This well-written book contains many references on the field of (global) random search techniques. (Kurt Marti, Mathematical Reviews, Issue 2008 j)<p> The aim of the book is to present the major methodological and theoretical developments in the field of stochastic global optimization including global random search and methods based on probabilistic assumptions about thes


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