Network Flows: Theory, Algorithms, and Applications

Network Flows: Theory, Algorithms, and Applications, 1/e

Ravindra K. Ahuja, Indian Institute of Technology, India
Thomas L. Magnanti, Massachusetts Institute of Technology
James B. Orlin, Massachusetts Institute of Technology

Published February, 1993 by Prentice Hall Engineering/Science/Mathematics

See other books about:
Optimization-Industrial Engineering

Network Programming-Industrial Engineering

Optimization-Computer Science

Network Programming-Decision Science

Optimization-Chemical Engineering

Summary

A comprehensive introduction to network flows that brings together the classic and the contemporary aspects of the field, and provides an integrative view of theory, algorithms, and applications.

Features

presents in-depth, self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including descriptions of polynomial-time algorithms for these core models.
emphasizes powerful algorithmic strategies and analysis tools such as data scaling, geometric improvement arguments, and potential function arguments.
provides an easy-to-understand descriptions of several important data structures, including d-heaps, Fibonacci heaps, and dynamic trees.
devotes a special chapter to conducting empirical testing of algorithms.
features over 150 applications of network flows to a variety of engineering, management, and scientific domains.
contains extensive reference notes and illustrations.

Table of Contents

1. Introduction.
2. Paths, Trees and Cycles.
3. Algorithm Design and Analysis.
4. Shortest Paths: Label Setting Algorithms.
5. Shortest Paths: Label Correcting Algorithms.
6. Maximum Flows: Basic Ideas.
7. Maximum Flows: Polynomial Algorithms.
8. Maximum Flows: Additional Topics.
9. Minimum Cost Flows: Basic Algorithms.
10. Minimum Cost Flows: Polynomial Algorithms.
11. Minimum Cost Flows: Network Simplex Algorithms.
12. Assignments and Matchings.
13. Minimum Spanning Trees.
14. Convex Cost Flows.
15. Generalized Flows.
16. Lagrangian Relaxation and Network Optimization.
17. Multicommodity Flows.
18. Computational Testing of Algorithms.
19. Additional Applications.
Appendix A: Data Structures.
Appendix B: NP-Completeness.
Appendix C: Linear Programming.
Index.