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Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications (SpringerBriefs in Optimization) - Tapa blanda
Sinopsis
Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications.
This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science.
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“The book is an outgrowth of the first author’s Ph.D. thesis, defended in 2011 ... . It is a well-written timely collection of state-of-the-art approximation algorithms for polynomial optimization problems ... . All of the approximation results of the book are conveniently summarized and listed in table 5.1 for quick reference, with a unified nomenclature introduced in sections 1.3.1 and 1.3.2.” (Didier Henrion, Mathematical Reviews, March, 2013)Reseña del editor
Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications. This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science.
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- EditorialSpringer
- Año de publicación2012
- ISBN 10 1461439833
- ISBN 13 9781461439837
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas132
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Approximation Methods for Polynomial Optimization
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Springer New York Jul 2012, 2012
ISBN 10: 1461439833
ISBN 13: 9781461439837
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications. This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science. 132 pp. Englisch. Nº de ref. del artículo: 9781461439837
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Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications (SpringerBriefs in Optimization)
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Approximation Methods for Polynomial Optimization : Models, Algorithms, and Applications
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Approximation Methods for Polynomial Optimization
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Springer New York, 2012
ISBN 10: 1461439833
ISBN 13: 9781461439837
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discuss some important subclasses of polynomial optimization models arising from various applicationsFocuses on approximations algorithms with guaranteed worst case performance analysisPresents a clear view of the basic ideas underlying the. Nº de ref. del artículo: 4198294
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Approximation Methods for Polynomial Optimization : Models, Algorithms, and Applications
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Springer New York, Springer US, 2012
ISBN 10: 1461439833
ISBN 13: 9781461439837
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications. This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science. Nº de ref. del artículo: 9781461439837
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Approximation Methods for Polynomial Optimization : Models, Algorithms, and Applications
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Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications
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Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications
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Approximation Methods for Polynomial Optimization
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Springer New York, Springer US Jul 2012, 2012
ISBN 10: 1461439833
ISBN 13: 9781461439837
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. Neuware -Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications.This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 132 pp. Englisch. Nº de ref. del artículo: 9781461439837
Cantidad disponible: 2 disponibles