Focusing on linear programming theory, this book draws on the research developments in three areas: linear and integer programming, numerical analysis, and the computational architectures which enable speedy, high-level algorithm design. Series: International Series in Operations Research & Management Science. Num Pages: 130 pages, biography. BIC Classification: PBUH; TGP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 9. Weight in Grams: 830. . 2002. Hardback. . . . .

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Bibliographic Details

Title: Potential Function Methods for Approximately Solving Linear Programming Problems
Publisher: Kluwer Academic Publishers
Publication Date: 2002
Language: English
ISBN 10: 1402071736
ISBN 13: 9781402071737
Binding: Hardcover
Condition: New

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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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