Network flows: theory, algorithms, and applications

By:

Ahuja, Ravindra K

Contributor(s):

Material type: Text

TextPublication details: Pearson India Education Services Pvt. Ltd. New Delhi 2014Description: xv, 846 pISBN:

9789332535152

Subject(s):

DDC classification:

658.4032 AHU

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.

List(s) this item appears in: IT & Decision Sciences | Public Policy & General Management

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	658.4032 AHU (Browse shelf(Opens below))	1	Available		000527

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Previous	658.403 SIL Data science and multiple criteria decision making approaches in finance	658.403 WAL Building decision support systems: using minizinc	658.40301 CHA Data science and productivity analytics	658.4032 AHU Network flows: theory, algorithms, and applications	658.4032 BAL Managerial decision modeling with spreadsheets	658.4032 KIM Business analytics for decision making	658.4032 MAT Business analytics for decision making	Next

Table of Content
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.

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.

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