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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice: 53 - Brossura
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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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Contenuti
List of Figures. List of Tables. Preface. 1. Introduction. 1. Early Algorithms. 2. The Exponential Potential Function - Key Ideas. 3. Recent Developments. 4. Computational Experiments. Appendices. Index.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer
- Data di pubblicazione2013
- ISBN 10 1475776721
- ISBN 13 9781475776720
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine136
- Contatto del produttorenon disponibile
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Condizione: 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. Codice articolo 4207915
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Taschenbuch. Condizione: 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. Codice articolo 9781475776720
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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. Condizione: 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. Codice articolo 9781475776720
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Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice
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Springer US, Springer US, 2013
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Taschenbuch. Condizione: 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. Codice articolo 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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