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 by Daniel Bienstock

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.

FORMAT
Hardcover LANGUAGE
English CONDITION
Brand New Publisher Description

This text 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. Since the 1990s, 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 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 has been a family of algorithms with solid theoretical foundations and with growing experimental success. This book examines these algorithms, starting with some of the very earliest examples through to the latest theoretical and computational developments.

Table of Contents

Early Algorithms.- The Exponential Potential Function - key Ideas.- Recent Developments.- Computational Experiments Using the Exponential Potential Function Framework.

Long Description

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.

Details ISBN1402071736 Author Daniel Bienstock Short Title POTENTIAL FUNCTION METHODS FOR Series International Series in Operations Research & Management Science Language English ISBN-10 1402071736 ISBN-13 9781402071737 Media Book Format Hardcover DEWEY 519.72 Series Number 53 Year 2002 Publication Date 2002-08-31 Subtitle Theory and Practice Country of Publication United States Pages 111 Place of Publication New York, NY DOI AU Release Date 2002-08-31 NZ Release Date 2002-08-31 US Release Date 2002-08-31 UK Release Date 2002-08-31 Edition Description 2002 ed. Edition 2002nd Illustrations XIX, 111 p. Audience Undergraduate Country of Origin US Product Class Description Mechanical Engineering Publisher Kluwer Academic Publishers Imprint Kluwer Academic Publishers Alternative 9780306476266
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