Overview

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.

Full Product Details

Author:   Daniel Bienstock
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2002 ed.
Volume:   53
Dimensions:   Width: 15.50cm , Height: 0.90cm , Length: 23.50cm
Weight:   0.830kg
ISBN:  

9781402071737

ISBN 10:   1402071736
Pages:   111
Publication Date:   31 August 2002
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

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

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