Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
Daniel Bienstock
ISBN 10: 1475776721 ISBN 13: 9781475776720
Editorial: Springer-Verlag New York Inc., 2013
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This item is printed on demand. New copy - Usually dispatched within 5-9 working days 219. N° de ref. del artículo C9781475776720
Sinopsis:
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.
Reseña del editor: 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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Detalles bibliográficos
Título: Potential Function Methods for Approximately...
Editorial: Springer-Verlag New York Inc.
Año de publicación: 2013
Encuadernación: Paperback / softback
Condición: New
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Condición: 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. Nº de ref. del artículo: 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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Springer US, Springer US Mär 2013, 2013
ISBN 10: 1475776721
ISBN 13: 9781475776720
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781475776720
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Springer US Mrz 2013, 2013
ISBN 10: 1475776721
ISBN 13: 9781475776720
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781475776720
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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
Publicado por
Springer US, Springer US, 2013
ISBN 10: 1475776721
ISBN 13: 9781475776720
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 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 (Paperback)
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Springer-Verlag New York Inc., New York, NY, 2013
ISBN 10: 1475776721
ISBN 13: 9781475776720
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Paperback. Condición: new. Paperback. 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. Potential Function Methods For Approximately Solving Linear Programming Problems breaks new ground in linear programming theory. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781475776720
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Potential Function Methods for Approximately Solving Linear Programming Problems
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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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Paperback. Condición: Brand New. 130 pages. 9.25x6.10x0.31 inches. In Stock. Nº de ref. del artículo: x-1475776721
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