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Algorithms in Java, Part 5 : Graph Algorithms

Algorithms in Java, Part 5 : Graph Algorithms - 3rd edition

ISBN13: 978-0201361216

Cover of Algorithms in Java, Part 5 : Graph Algorithms 3RD 04 (ISBN 978-0201361216)
ISBN13: 978-0201361216
ISBN10: 0201361213
Cover type: Paperback
Edition/Copyright: 3RD 04
Publisher: Addison-Wesley Longman, Inc.
Published: 2004
International: No

List price: $59.99

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Algorithms in Java, Part 5 : Graph Algorithms - 3RD 04 edition

ISBN13: 978-0201361216

Robert Sedgewick

ISBN13: 978-0201361216
ISBN10: 0201361213
Cover type: Paperback
Edition/Copyright: 3RD 04
Publisher: Addison-Wesley Longman, Inc.

Published: 2004
International: No
Summary

Algorithms in Java, Third Edition, Part 5: Graph Algorithms, contains six chapters that cover graph properties and types, graph search, directed graphs, minimal spanning trees, shortest paths, and networks. The descriptions here are intended to give students an understanding of the basic properties of as broad a range of fundamental graph algorithms as possible. In the third edition, many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. Unlike any other book on algorithms, not only will students get practical information on using algorithms in their work, they can also be assured that these algorithms rest on the most solid scientific foundations. And a new emphasis on abstract data types throughout the books makes the programs more broadly useful and relevant in modern object-oriented programming environments.

This book is useful as a text early in the computer science curriculum, after students have acquired basic programming skills and familiarity with computer systems, but before they have taken specialized courses in advanced areas of computer science or computer applications. There is sufficient coverage of basic material for the book to be used to teach data structures to beginners, and there is sufficient detail and coverage of advanced material for the book to be used to teach the design and analysis of algorithms to upper-level students. Some instructors may wish to emphasize implementations and practical concerns; others may wish to emphasize analysis and theoretical concepts. For a more comprehensive course, this book is also available in a special bundle with Parts 1-4 (ISBN for bundle of Parts 1-4 and Part 5 is 0201775786); thereby instructors can cover fundamentals, data structures, sorting, searching, and graph algorithms in one consistent style.

Features :

  • Part 5 of Sedgewick's seminal work on Algorithms is completely rewritten and now available in Java.
  • Enhanced presentation with a new text design and detailed, innovative figures, with accompanying commentary.
  • Thousands of new exercises, hundreds of new figures, dozens of new programs.
  • Source code is available on the web.

Author Bio

Sedgewick, Robert : Princeton University

Table of Contents

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.

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