Algorithms in Java, Part 5
Graph Algorithms
3rd Edition
Published on 24. July 2003
Book
Paperback/Softback
528 pages
978-0-201-36121-6 (ISBN)
Description
Robert Sedgewick, along with Donald Knuth, is one of the very few people with a world-wide reputation for their contributions to the field of computer algorithms. This book is the second of three volumes that survey the most important computer algorithms in use today. Much more than a standard revision, this is a major rewrite. The material is more than five times as long as in the previous edition, which was only available in C and C++. KEY TOPICS: Sedgewick has added a wealth of new exercises, hundreds of new figures, and dozens of new programs. This volume, Part 5, covers graph algorithms, which are pervasive in modern computing appications. 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 on the Web. The C and C++ versions of this volume have been previously published. Unlike any other book on algorithms, not only will programmers get practical information on using algorithms in their work, they can also be assured that these algorithms rest on the most solid scientific foundations. MARKET: Both professional programmers and computer science students.
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Content
PART V. GRAPH ALGORITHMS.
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 Flow.
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.
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 Flow.
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.