Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice - Theory and Practice

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.

List of contents

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

Summary

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.

Product details

• Authors: Daniel Bienstock
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 26.06.2009
• EAN: 9781402071737
• ISBN: 978-1-4020-7173-7
• No. of pages: 111
• Weight: 376 g
• Illustrations: XIX, 111 p.
• Series: International Series in Operations Research & Management Science; International Series in Operations Research & Management Science; International Series in Operations Research Management Science
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; Operations Research, C, Optimization, Operations Research/Decision Theory, Operations Research and Decision Theory, Mathematics and Statistics, Management & management techniques, Operations Research, Management Science, Management decision making, Management science, Operational research, Decision Making, Mathematical optimization, Calculus of Variations and Optimization, Calculus of variations, Calculus of Variations and Optimal Control; Optimization