CHAPTER 25 Weighted Graphs and Applications Objectives â¢ To ...

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13 "Atlanta", "Miami", "Dallas", "Houston"}; 14 15 // Edge array for graph in Figure 25.1 16 int edges[][3] = { 17 {0, 1, 807}, {0, 3, 1331}, {0, 5, 2097}, 18 {1, 0, 807}, {1, 2, 381}, {1, 3, 1267}, 19 {2, 1, 381}, {2, 3, 1015}, {2, 4, 1663}, {2, 10, 1435}, 20 {3, 0, 1331}, {3, 1, 1267}, {3, 2, 1015}, {3, 4, 599}, 21 {3, 5, 1003}, 22 {4, 2, 1663}, {4, 3, 599}, {4, 5, 533}, {4, 7, 1260}, 23 {4, 8, 864}, {4, 10, 496}, 24 {5, 0, 2097}, {5, 3, 1003}, {5, 4, 533}, 25 {5, 6, 983}, {5, 7, 787}, 26 {6, 5, 983}, {6, 7, 214}, 27 {7, 4, 1260}, {7, 5, 787}, {7, 6, 214}, {7, 8, 888}, 28 {8, 4, 864}, {8, 7, 888}, {8, 9, 661}, 29 {8, 10, 781}, {8, 11, 810}, 30 {9, 8, 661}, {9, 11, 1187}, 31 {10, 2, 1435}, {10, 4, 496}, {10, 8, 781}, {10, 11, 239}, 32 {11, 8, 810}, {11, 9, 1187}, {11, 10, 239} 33 }; 34 35 // 23 undirected edges in Figure 25.1 36 const int NUMBER_OF_EDGES = 46; 37 38 // Create a vector for vertices 39 vector vectorOfVertices(12); 40 copy(vertices, vertices + 12, vectorOfVertices.begin()); 41 42 // Create a vector for edges 43 vector edgeVector; 44 for (int i = 0; i < NUMBER_OF_EDGES; i++) 45 edgeVector.push_back(WeightedEdge(edges[i][0], 46 edges[i][1], edges[i][2])); 47 48 WeightedGraph graph1(vectorOfVertices, edgeVector); 49 cout
72 edges2[i][1], edges2[i][2])); 73 74 WeightedGraph graph2(5, edgeVector2); // 5 vertices in graph2 75 76 cout
Page 1 and 2: CHAPTER 25 Weighted Graphs and Appl
Page 3 and 4: acquainted with weighted graphs usi
Page 5 and 6: 7 { 8 public: 9 double weight; // T
Page 7 and 8: Graph Defined in Figure 24.7. Weigh
Page 9 and 10: 72 for (unsigned i = 0; i < edges.s
Page 11: 189 u = i; 190 } 191 } 192 193 if (
Page 15 and 16: vector neighbors; neighbors[0].push
Page 17 and 18: 10 Add u to T; 11 for (each v not i
Page 19 and 20: 1 10 2 cost 0 9 5 9 7 5 8 T 0 1 2 3
Page 21 and 22: (g) NOTE: A minimum spanning tree i
Page 23 and 24: The MST class extends the Tree clas
Page 25 and 26: 81 vector edgeVector2; 82 for (int
Page 27 and 28: 25.5 Finding Shortest Paths The sh
Page 29 and 30: (a) Before moving u to T (b) After
Page 31 and 32: Now T contains {1, 2, 0}. Vertex 6
Page 33 and 34: As you see, the algorithm essential
Page 35 and 36: priority queues, we can implement t
Page 37 and 38: 57 const int NUMBER_OF_EDGES = 46;
Page 39 and 40: 25.12 What happens to the getShorte
Page 41 and 42: and flipACell(&node, row, column) d
Page 43 and 44: The getNumberOfFlips(int u) functio
Page 45 and 46: 4. Dijkstra’s algorithm starts se
Page 47 and 48: The vertices and edges of a weighte
Page 49 and 50: Input: a weighted graph G = (V, E)

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CHAPTER 25 Weighted Graphs and Applications Objectives â¢ To ...