Algorithms in Java (E-BOOK) Robert Sedgewick.

By: Sedgewick, RobertPublisher: Boston : Addison-Wesley, c2003-<2004>Edition: 3rd edDescription: v. <1-2 > : ill. ; 24 cmISBN: 0201361205Subject(s): Computer algorithms | Java (Computer program language) | Algorithms in Java (E-BOOK)DDC classification: 005.133
Incomplete contents:
Preface Algorithms Scope Use in the Curriculum Algorithms of Practical Use Programming Language Acknowledgments Java Consultant's Preface Notes on Exercises Part V: Graph Algorithms Chapter 17. Graph Properties and Types Section 17.1. Glossary Section 17.2. Graph ADT Section 17.3. Adjacency-Matrix Representation Section 17.4. Adjacency-Lists Representation Section 17.5. Variations, Extensions, and Costs Section 17.6. Graph Generators Section 17.7. Simple, Euler, and Hamilton Paths Section 17.8. Graph-Processing Problems Chapter 18. Graph Search Section 18.1. Exploring a Maze Section 18.2. Depth-First Search Section 18.3. Graph-Search ADT Methods Section 18.4. Properties of DFS Forests Section 18.5. DFS Algorithms Section 18.6. Separability and Biconnectivity Section 18.7. Breadth-First Search Section 18.8. Generalized Graph Search Section 18.9. Analysis of Graph Algorithms Chapter 19. Digraphs and DAGs Exercises Section 19.1. Glossary and Rules of the Game Section 19.2. Anatomy of DFS in Digraphs Section 19.3. Reachability and Transitive Closure Section 19.4. Equivalence Relations and Partial Orders Section 19.5. DAGs Section 19.6. Topological Sorting Section 19.7. Reachability in DAGs Section 19.8. Strong Components in Digraphs Section 19.9. Transitive Closure Revisited Section 19.10. Perspective Chapter 20. Minimum Spanning Trees Exercises Section 20.1. Representations Section 20.2. Underlying Principles of MST Algorithms Section 20.3. Prim's Algorithm and Priority-First Search Section 20.4. Kruskal's Algorithm Section 20.5. Boruvka's Algorithm Section 20.6. Comparisons and Improvements Section 20.7. Euclidean MST Chapter 21. Shortest Paths Exercises Section 21.1. Underlying Principles Section 21.2. Dijkstra's Algorithm Section 21.3. All-Pairs Shortest Paths Section 21.4. Shortest Paths in Acyclic Networks Section 21.5. Euclidean Networks Section 21.6. Reduction Section 21.7. Negative Weights Section 21.8. Perspective Chapter 22. Network Flow Section 22.1. Flow Networks Section 22.2. Augmenting-Path Maxflow Algorithms Section 22.3. Preflow-Push Maxflow Algorithms Section 22.4. Maxflow Reductions Section 22.5. Mincost Flows Section 22.6. Network Simplex Algorithm Section 22.7. Mincost-Flow Reductions Section 22.8. Perspective
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Item type Current location Home library Collection Call number URL Status Date due Barcode Item holds
Book Book Military College of Signals (MCS)
Military College of Signals (MCS)
NFIC 05.133 SED (Browse shelf) Link to resource Available MCSEB-103
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Preface Algorithms Scope Use in the Curriculum Algorithms of Practical Use Programming Language Acknowledgments Java Consultant's Preface Notes on Exercises Part V: Graph Algorithms Chapter 17. Graph Properties and Types Section 17.1. Glossary Section 17.2. Graph ADT Section 17.3. Adjacency-Matrix Representation Section 17.4. Adjacency-Lists Representation Section 17.5. Variations, Extensions, and Costs Section 17.6. Graph Generators Section 17.7. Simple, Euler, and Hamilton Paths Section 17.8. Graph-Processing Problems Chapter 18. Graph Search Section 18.1. Exploring a Maze Section 18.2. Depth-First Search Section 18.3. Graph-Search ADT Methods Section 18.4. Properties of DFS Forests Section 18.5. DFS Algorithms Section 18.6. Separability and Biconnectivity Section 18.7. Breadth-First Search Section 18.8. Generalized Graph Search Section 18.9. Analysis of Graph Algorithms Chapter 19. Digraphs and DAGs Exercises Section 19.1. Glossary and Rules of the Game Section 19.2. Anatomy of DFS in Digraphs Section 19.3. Reachability and Transitive Closure Section 19.4. Equivalence Relations and Partial Orders Section 19.5. DAGs Section 19.6. Topological Sorting Section 19.7. Reachability in DAGs Section 19.8. Strong Components in Digraphs Section 19.9. Transitive Closure Revisited Section 19.10. Perspective Chapter 20. Minimum Spanning Trees Exercises Section 20.1. Representations Section 20.2. Underlying Principles of MST Algorithms Section 20.3. Prim's Algorithm and Priority-First Search Section 20.4. Kruskal's Algorithm Section 20.5. Boruvka's Algorithm Section 20.6. Comparisons and Improvements Section 20.7. Euclidean MST Chapter 21. Shortest Paths Exercises Section 21.1. Underlying Principles Section 21.2. Dijkstra's Algorithm Section 21.3. All-Pairs Shortest Paths Section 21.4. Shortest Paths in Acyclic Networks Section 21.5. Euclidean Networks Section 21.6. Reduction Section 21.7. Negative Weights Section 21.8. Perspective Chapter 22. Network Flow Section 22.1. Flow Networks Section 22.2. Augmenting-Path Maxflow Algorithms Section 22.3. Preflow-Push Maxflow Algorithms Section 22.4. Maxflow Reductions Section 22.5. Mincost Flows Section 22.6. Network Simplex Algorithm Section 22.7. Mincost-Flow Reductions Section 22.8. Perspective

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