Improved Primal Simplex Algorithms for Shortest Path, Assignment and Minimum
Language: English
Published by Forgotten Books, 2022
- Softcover
- New
Seller: Forgotten Books, London, United KingdomForgotten Books
AbeBooks seller since June 2, 2021
Condition: New
US$ 17.27
Quantity: Over 20 available
Add to basketItem description from seller
Print on Demand. This book introduces a new and improved primal simplex pivot rule for the minimum cost flow problem, demonstrating its worst-case complexity and analyzing its implementation for the shortest path and assignment problems. The author expands on existing research and presents a detailed complexity analysis, providing valuable insights into the potential of this rule. This book positions itself as a significant contribution to the field of network optimization and is essential reading for researchers and practitioners interested in efficient algorithms for network flow problems. Its in-depth exploration of the scaling pivot rule and its applications make it an invaluable resource for advancing the theory and practice of network optimization. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. …
Seller Inventory # 9781332265107_0
- Title
- Improved Primal Simplex Algorithms for Shortest Path, Assignment and Minimum
- Author
- Ravindra K. Ahuja, James B. Orlin
- Publisher
- Forgotten Books
- Publication year
- 2022
- Condition
- New
- Book Type
- print-on-demand item
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1332265103
- ISBN 13
- 9781332265107
- Seller catalogs
- Calculus
A practical look at faster network optimization methods for flow and path problems.
This work presents a new primal scaling pivot rule for the network simplex algorithm and shows how it improves worst‑case performance for the minimum cost flow problem, with specialized results for the assignment and shortest path problems. It blends theory with concrete bounds and practical implementation ideas.
The approach centers on scaling the pivot rule to maintain strong feasibility and to reduce the number of pivots. By embedding scaling into Dantzig’s rule, the method achieves competitive running times and clearer performance guarantees across key combinatorial problems. The discussion covers data structures, complexity, and how the technique translates to specific problem settings.
- Introduction of a scaling network simplex pivot rule for flow problems
- Specialized results for the assignment and shortest path problems
- Analyses of pivot counts and running times with practical implementation notes
- Discussion of data structures and feasibility concepts to support efficient pivots
Ideal for readers seeking a solid, implementable approach to network optimization and its common applications.
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Forgotten Books
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Forgotten Books’ Classic Reprint Series utilizes the latest technology to regenerate facsimiles of historically important writings. Careful attention has been made to accurately preserve the original format of each page whilst digitally enhancing the quality of the aged text.
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