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Algorithms in C, Part 5: Graph Algorithms, 3rd edition

Published by Addison-Wesley Professional (August 16, 2001) © 2002

  • Robert Sedgewick Princeton University

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Graph algorithms are increasingly critical for a wide range of applications, such as network connectivity, circuit design, scheduling, transaction processing, and resource allocation. In the third edition, many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. Source code for the implementations is available via the Internet.



Preface.


Notes on Exercises.


17. Graph Properties and Types.

Glossary.

Graph ADT.

Adjacency-Matrix Representation.

Adjacency-Lists Representation.

Variations, Extensions, and Costs.

Graph Generators.

Simple, Euler, and Hamilton Paths.

Graph-Processing Problems.



18. Graph Search.

Exploring a Maze.

Depth-First Search.

Graph-Search ADT Functions.

Properties of DFS Forests.

DFS Algorithms.

Separability and Biconnectivity.

Breadth-First Search.

Generalized Graph Search.

Analysis of Graph Algorithms.



19. Digraphs and DAGs.

Glossary and Rules of the Game.

Anatomy of DFS in Digraphs.

Reachability and Transitive Closure.

Equivalence Relations and Partial Orders.

DAGs.

Topological Sorting.

Reachability in DAGs.

Strong Components in Digraphs.

Transitive Closure Revisited.

Perspective.



20. Minimum Spanning Trees.

Representations.

Underlying Principles of MST Algorithms.

Prim's Algorithm and Priority-First Search.

Kruskal's Algorithm.

Boruvka's Algorithm.

Comparisons and Improvements.

Euclidean MST.



21. Shortest Paths.

Underlying Principles.

Dijkstra's algorithm.

All-Pairs Shortest Paths.

Shortest Paths in Acyclic Networks.

Euclidean Networks.

Reduction.

Negative Weights.

Perspective.



22. Network Flows.

Flow Networks.

Augmenting-Path Maxflow Algorithms.

Preflow-Push Maxflow Algorithms.

Maxflow Reductions.

Mincost Flows.

Network Simplex Algorithm.

Mincost-Flow Reductions.

Perspective.



References for Part Five.


Index. 0201316633T09172001

Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University. He is a Director of Adobe Systems and has served on the research staffs at Xerox PARC, IDA, and INRIA. He earned his Ph.D from Stanford University under Donald E. Knuth.


0201316633AB06262002

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