Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice - Couverture souple
Livre 42 sur 323: International Series in Operations Research & Management Science
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Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice (eng)
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice (International Series in Operations Research & Management Science)
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments. 136 pp. Englisch. N° de réf. du vendeur 9781475776720
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical ana. N° de réf. du vendeur 4207915
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice (International Series in Operations Research & Management Science)
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Taschenbuch. Etat : Neu. Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice | Daniel Bienstock | Taschenbuch | xix | Englisch | 2013 | Springer | EAN 9781475776720 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 105648959
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Springer US, Springer US Mär 2013, 2013
ISBN 10 : 1475776721
ISBN 13 : 9781475776720
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 136 pp. Englisch. N° de réf. du vendeur 9781475776720
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
Edité par
Springer US, Springer US, 2013
ISBN 10 : 1475776721
ISBN 13 : 9781475776720
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. The book draws on the research developments in three broad areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. During the last ten years, a new body of research within the field of optimization research has emerged, which seeks to develop good approximation algorithms for classes of linear programming problems. This work both has roots in fundamental areas of mathematical programming and is also framed in the context of the modern theory of algorithms. The result of this work, in which Daniel Bienstock has been very much involved, has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book will examine these algorithms, starting with some of the very earliest examples, and through the latest theoretical and computational developments. N° de réf. du vendeur 9781475776720
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