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Stochastic Adaptive Search for Global Optimization - Z.B. Zabinsky

Stochastic Adaptive Search for Global Optimization

(Autor)

Buch | Softcover
224 Seiten
2013 | Softcover reprint of the original 1st ed. 2003
Springer-Verlag New York Inc.
978-1-4613-4826-9 (ISBN)
CHF 149,75 inkl. MwSt
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In this book, an attempt is made to describe the theoretical prop­ erties of several stochastic adaptive search methods. Chapter 6 discusses algorithms, based on the Hit-and-Run sampling method, that have been developed to approximate the ideal performance of pure random search.
The field of global optimization has been developing at a rapid pace. There is a journal devoted to the topic, as well as many publications and notable books discussing various aspects of global optimization. This book is intended to complement these other publications with a focus on stochastic methods for global optimization. Stochastic methods, such as simulated annealing and genetic algo­ rithms, are gaining in popularity among practitioners and engineers be­ they are relatively easy to program on a computer and may be cause applied to a broad class of global optimization problems. However, the theoretical performance of these stochastic methods is not well under­ stood. In this book, an attempt is made to describe the theoretical prop­ erties of several stochastic adaptive search methods. Such a theoretical understanding may allow us to better predict algorithm performance and ultimately design new and improved algorithms. This book consolidates a collection of papers on the analysis and de­ velopment of stochastic adaptive search. The first chapter introduces random search algorithms. Chapters 2-5 describe the theoretical anal­ ysis of a progression of algorithms. A main result is that the expected number of iterations for pure adaptive search is linear in dimension for a class of Lipschitz global optimization problems. Chapter 6 discusses algorithms, based on the Hit-and-Run sampling method, that have been developed to approximate the ideal performance of pure random search. The final chapter discusses several applications in engineering that use stochastic adaptive search methods.
Reihe/Serie Nonconvex Optimization and Its Applications ; 72
Zusatzinfo XVIII, 224 p.
Verlagsort New York, NY
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Mathematik / Informatik Mathematik Graphentheorie
ISBN-10 1-4613-4826-9 / 1461348269
ISBN-13 978-1-4613-4826-9 / 9781461348269
Zustand Neuware
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