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Graph

Graph. Charles Lin. Agenda. Graph Representation DFS B FS Dijkstra A* Search Bellman-Ford Floyd- Warshall Iterative? Non-iterative? MST Flow – Edmond-Karp. Graph Representation. Adjacency Matrix bool way[100][100]; cin >> i >> j; way[i][j] = true;. Graph Representation.

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Graph

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  1. Graph Charles Lin

  2. Agenda • Graph Representation • DFS • BFS • Dijkstra • A* Search • Bellman-Ford • Floyd-Warshall • Iterative? Non-iterative? • MST • Flow – Edmond-Karp

  3. Graph Representation • Adjacency Matrix • bool way[100][100]; • cin >> i >> j; • way[i][j] = true;

  4. Graph Representation • Adjacency Linked List • vector<int> v[100]; • cin >> i >> j; • v[i].push_back(j);

  5. Graph Representation • Edge List struct Edge { intStart_Vertex, End_Vertex; } edge[10000]; cin >> edge[i].Start_Vertex >> edge[i].End_Vertex;

  6. Graph Representation

  7. Graph Theory 2 B D 10 A 8 4 1 7 9 C E 3 2

  8. Graph Theory • Mission: To go from Point A to Point E • How?

  9. Depth First Search (DFS) • Structure to use: Stack • See “The House of Santa Claus”

  10. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  11. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  12. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  13. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  14. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  15. Depth First Search (DFS) 2 B D 10 A 8 4 1 B is visited already 7 9 C E 3 2

  16. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  17. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  18. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  19. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2

  20. Depth First Search (DFS) 2 B D 10 A 8 4 1 7 9 C E 3 2 We find a path from Point A to Point E, but ……

  21. Depth First Search (DFS) int main() { memset(Visited, 0, sizeof(Visited)); // Input Handling (GOAL = ?) DFS(0); } stack<int> s; bool Visited[MAX]; void DFS(int u) { s.push(u); if (u == GOAL) { for (int x = 0; x < s.size(); x++) printf(“%d “, s[x]); return ; } for (int x = 0; x < MAX; x++) if (!Visited[x]) { Visited[x] = true; DFS(x); Visited[x] = false; } s.pop();} Very Important It needs to be restored for other points to traverse, or the path may not be found

  22. Depth First Search (DFS) • Usage: • Finding a path from start to destination (NOT RECOMMENDED – TLE) • Topological Sort (T-Sort) • Strongly-Connected Component (SCC)

  23. Depth First Search (DFS) • Topological Sort • Directed Acyclic Graph (DAG) • Find the order of nodes such that for each node, every parent is before that node on the list • Dump Method: Check for root of residual graph (Do it n times) • Better Method: Reverse of finishing time

  24. Depth First Search (DFS) T-Sort: 2 B D 10 A 8 4 1 7 9 C E 3 2 Cycle Exists !!!

  25. Depth First Search (DFS) T-Sort: B D A C E OK

  26. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: NONE

  27. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: NONE

  28. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: NONE

  29. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: NONE

  30. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: NONE

  31. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E

  32. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D

  33. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B

  34. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B

  35. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B

  36. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B

  37. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B

  38. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B, C

  39. Depth First Search (DFS) T-Sort: B D A C E Things in output stack: E, D, B, C, A T-Sort Output: A, C, B, D, E

  40. Depth First Search (DFS) • Strongly Connected Components • Directed Graph • Find groups of nodes such that in each group, every node has an edge to every other node

  41. Depth First Search (DFS) • Strongly Connected Components • Method: DFS twice • Do DFS on Graph G, record finishing time of node • Do DFS on Graph GT, by decreasing finish time • Output the vertices

  42. Depth First Search (DFS) • Strongly Connected Components • Note: After grouping the vertices, the new nodes form a Directed Acyclic Graph • Problem: Where’s the back button

  43. Breadth First Search (BFS) • Structure to use: Queue

  44. Breadth First Search (BFS) Things in queue: A, C 3 A, B 10 2 B D 10 A 8 4 1 7 9 C E 3 2

  45. Breadth First Search (BFS) Things in queue: A, B 10 A, C, E5 A, C, B 7 A, C, D 8 2 B D 10 A 8 4 1 7 9 C E 3 2

  46. Breadth First Search (BFS) Things in queue: A, C, E5 A, C, B 7 A, C, D 8 A, B, C 11 A, B, D 12 2 B D 10 A 8 4 1 7 9 C E 3 2

  47. Breadth First Search (BFS) Things in queue: A, C, B 7 A, C, D 8 A, B, C 11 A, B, D 12 2 B D 10 A 8 4 1 7 9 C E 3 2 We are done !!!

  48. Breadth First Search (BFS) • Application: • Finding shortest path • Flood-Fill

  49. Dijkstra • Structure to use: Priority Queue • Consider the past • The length of path visited so far • No negative edges allowed

  50. Dijkstra Things in priority queue: A, C 3 A, B 10 2 B D 10 A 8 4 1 7 9 Current Route: A C E 3 2

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