Potential Function Methods for Approximately Solving Linear Programming Problems

The Nile on
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
Paperback LANGUAGE
English CONDITION
Brand New Publisher 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.

Table of Contents

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

Promotional

Springer Book Archives

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 ISBN1475776721 Author Daniel Bienstock Language English Edition 02200th Subtitle Theory and Practice ISBN-10 1475776721 ISBN-13 9781475776720 Short Title POTENTIAL FUNCTION METHODS FOR Series International Series in Operations Research & Management Science Media Book DEWEY 519.72 Series Number 53 Year 2013 Publication Date 2013-03-17 Imprint Springer-Verlag New York Inc. Place of Publication New York, NY Country of Publication United States Illustrations XIX, 111 p. AU Release Date 2013-03-17 NZ Release Date 2013-03-17 US Release Date 2013-03-17 UK Release Date 2013-03-17 Pages 111 Publisher Springer-Verlag New York Inc. Edition Description Softcover reprint of the original 1st ed. 2002 Format Paperback Alternative 9781402071737 Audience Professional & Vocational Country of Origin NL Product Class Description Mathematics
We\'ve got this

At The Nile, if you\'re looking for it, we\'ve got it.
With fast shipping, low prices, friendly service and well over a million items - you\'re bound to find what you want, at a price you\'ll love!

TheNile_Item_ID:96342606;