// C++ program for Dijkstra's single source shortest path // algorithm. The program is for adjacency matrix // representation of the graph #include  using namespace std; #include  // Number of vertices in the graph #define V 9 // A utility function to find the vertex with minimum // distance value, from the set of vertices not yet included // in shortest path tree int minDistance(int dist[], bool sptSet[]) {  // Initialize min value  int min = INT_MAX, min_index;  for (int v = 0; v < V; v++)  if (sptSet[v] == false && dist[v] <= min)  min = dist[v], min_index = v;  return min_index; } // A utility function to print the constructed distance // array void printSolution(int dist[]) {  cout << 'Vertex 	 Distance from Source' << endl;  for (int i = 0; i < V; i++)  cout << i << ' 				' << dist[i] << endl; } // Function that implements Dijkstra's single source // shortest path algorithm for a graph represented using // adjacency matrix representation void dijkstra(int graph[V][V], int src) {  int dist[V]; // The output array. dist[i] will hold the  // shortest  // distance from src to i  bool sptSet[V]; // sptSet[i] will be true if vertex i is  // included in shortest  // path tree or shortest distance from src to i is  // finalized  // Initialize all distances as INFINITE and stpSet[] as  // false  for (int i = 0; i < V; i++)  dist[i] = INT_MAX, sptSet[i] = false;  // Distance of source vertex from itself is always 0  dist[src] = 0;  // Find shortest path for all vertices  for (int count = 0; count < V - 1; count++) {  // Pick the minimum distance vertex from the set of  // vertices not yet processed. u is always equal to  // src in the first iteration.  int u = minDistance(dist, sptSet);  // Mark the picked vertex as processed  sptSet[u] = true;  // Update dist value of the adjacent vertices of the  // picked vertex.  for (int v = 0; v < V; v++)  // Update dist[v] only if is not in sptSet,  // there is an edge from u to v, and total  // weight of path from src to v through u is  // smaller than current value of dist[v]  if (!sptSet[v] && graph[u][v]  && dist[u] != INT_MAX  && dist[u] + graph[u][v] < dist[v])  dist[v] = dist[u] + graph[u][v];  }  // print the constructed distance array  printSolution(dist); } // driver's code int main() {  /* Let us create the example graph discussed above */  int graph[V][V] = { { 0, 4, 0, 0, 0, 0, 0, 8, 0 },  { 4, 0, 8, 0, 0, 0, 0, 11, 0 },  { 0, 8, 0, 7, 0, 4, 0, 0, 2 },  { 0, 0, 7, 0, 9, 14, 0, 0, 0 },  { 0, 0, 0, 9, 0, 10, 0, 0, 0 },  { 0, 0, 4, 14, 10, 0, 2, 0, 0 },  { 0, 0, 0, 0, 0, 2, 0, 1, 6 },  { 8, 11, 0, 0, 0, 0, 1, 0, 7 },  { 0, 0, 2, 0, 0, 0, 6, 7, 0 } };  // Function call  dijkstra(graph, 0);  return 0; } // This code is contributed by shivanisinghss2110>

// C program for Dijkstra's single source shortest path // algorithm. The program is for adjacency matrix // representation of the graph #include  #include  #include  // Number of vertices in the graph #define V 9 // A utility function to find the vertex with minimum // distance value, from the set of vertices not yet included // in shortest path tree int minDistance(int dist[], bool sptSet[]) {  // Initialize min value  int min = INT_MAX, min_index;  for (int v = 0; v < V; v++)  if (sptSet[v] == false && dist[v] <= min)  min = dist[v], min_index = v;  return min_index; } // A utility function to print the constructed distance // array void printSolution(int dist[]) {  printf('Vertex 		 Distance from Source
');  for (int i = 0; i < V; i++)  printf('%d 				 %d
', i, dist[i]); } // Function that implements Dijkstra's single source // shortest path algorithm for a graph represented using // adjacency matrix representation void dijkstra(int graph[V][V], int src) {  int dist[V]; // The output array. dist[i] will hold the  // shortest  // distance from src to i  bool sptSet[V]; // sptSet[i] will be true if vertex i is  // included in shortest  // path tree or shortest distance from src to i is  // finalized  // Initialize all distances as INFINITE and stpSet[] as  // false  for (int i = 0; i < V; i++)  dist[i] = INT_MAX, sptSet[i] = false;  // Distance of source vertex from itself is always 0  dist[src] = 0;  // Find shortest path for all vertices  for (int count = 0; count < V - 1; count++) {  // Pick the minimum distance vertex from the set of  // vertices not yet processed. u is always equal to  // src in the first iteration.  int u = minDistance(dist, sptSet);  // Mark the picked vertex as processed  sptSet[u] = true;  // Update dist value of the adjacent vertices of the  // picked vertex.  for (int v = 0; v < V; v++)  // Update dist[v] only if is not in sptSet,  // there is an edge from u to v, and total  // weight of path from src to v through u is  // smaller than current value of dist[v]  if (!sptSet[v] && graph[u][v]  && dist[u] != INT_MAX  && dist[u] + graph[u][v] < dist[v])  dist[v] = dist[u] + graph[u][v];  }  // print the constructed distance array  printSolution(dist); } // driver's code int main() {  /* Let us create the example graph discussed above */  int graph[V][V] = { { 0, 4, 0, 0, 0, 0, 0, 8, 0 },  { 4, 0, 8, 0, 0, 0, 0, 11, 0 },  { 0, 8, 0, 7, 0, 4, 0, 0, 2 },  { 0, 0, 7, 0, 9, 14, 0, 0, 0 },  { 0, 0, 0, 9, 0, 10, 0, 0, 0 },  { 0, 0, 4, 14, 10, 0, 2, 0, 0 },  { 0, 0, 0, 0, 0, 2, 0, 1, 6 },  { 8, 11, 0, 0, 0, 0, 1, 0, 7 },  { 0, 0, 2, 0, 0, 0, 6, 7, 0 } };  // Function call  dijkstra(graph, 0);  return 0; }>

// A Java program for Dijkstra's single source shortest path // algorithm. The program is for adjacency matrix // representation of the graph import java.io.*; import java.lang.*; import java.util.*; class ShortestPath {  // A utility function to find the vertex with minimum  // distance value, from the set of vertices not yet  // included in shortest path tree  static final int V = 9;  int minDistance(int dist[], Boolean sptSet[])  {  // Initialize min value  int min = Integer.MAX_VALUE, min_index = -1;  for (int v = 0; v < V; v++)  if (sptSet[v] == false && dist[v] <= min) {  min = dist[v];  min_index = v;  }  return min_index;  }  // A utility function to print the constructed distance  // array  void printSolution(int dist[])  {  System.out.println(  'Vertex 		 Distance from Source');  for (int i = 0; i < V; i++)  System.out.println(i + ' 		 ' + dist[i]);  }  // Function that implements Dijkstra's single source  // shortest path algorithm for a graph represented using  // adjacency matrix representation  void dijkstra(int graph[][], int src)  {  int dist[] = new int[V]; // The output array.  // dist[i] will hold  // the shortest distance from src to i  // sptSet[i] will true if vertex i is included in  // shortest path tree or shortest distance from src  // to i is finalized  Boolean sptSet[] = new Boolean[V];  // Initialize all distances as INFINITE and stpSet[]  // as false  for (int i = 0; i < V; i++) {  dist[i] = Integer.MAX_VALUE;  sptSet[i] = false;  }  // Distance of source vertex from itself is always 0  dist[src] = 0;  // Find shortest path for all vertices  for (int count = 0; count < V - 1; count++) {  // Pick the minimum distance vertex from the set  // of vertices not yet processed. u is always  // equal to src in first iteration.  int u = minDistance(dist, sptSet);  // Mark the picked vertex as processed  sptSet[u] = true;  // Update dist value of the adjacent vertices of  // the picked vertex.  for (int v = 0; v < V; v++)  // Update dist[v] only if is not in sptSet,  // there is an edge from u to v, and total  // weight of path from src to v through u is  // smaller than current value of dist[v]  if (!sptSet[v] && graph[u][v] != 0  && dist[u] != Integer.MAX_VALUE  && dist[u] + graph[u][v] < dist[v])  dist[v] = dist[u] + graph[u][v];  }  // print the constructed distance array  printSolution(dist);  }  // Driver's code  public static void main(String[] args)  {  /* Let us create the example graph discussed above  */  int graph[][]  = new int[][] { { 0, 4, 0, 0, 0, 0, 0, 8, 0 },  { 4, 0, 8, 0, 0, 0, 0, 11, 0 },  { 0, 8, 0, 7, 0, 4, 0, 0, 2 },  { 0, 0, 7, 0, 9, 14, 0, 0, 0 },  { 0, 0, 0, 9, 0, 10, 0, 0, 0 },  { 0, 0, 4, 14, 10, 0, 2, 0, 0 },  { 0, 0, 0, 0, 0, 2, 0, 1, 6 },  { 8, 11, 0, 0, 0, 0, 1, 0, 7 },  { 0, 0, 2, 0, 0, 0, 6, 7, 0 } };  ShortestPath t = new ShortestPath();  // Function call  t.dijkstra(graph, 0);  } } // This code is contributed by Aakash Hasija>

# Python program for Dijkstra's single # source shortest path algorithm. The program is # for adjacency matrix representation of the graph # Library for INT_MAX import sys class Graph(): def __init__(self, vertices): self.V = vertices self.graph = [[0 for column in range(vertices)] for row in range(vertices)] def printSolution(self, dist): print('Vertex 	Distance from Source') for node in range(self.V): print(node, '	', dist[node]) # A utility function to find the vertex with # minimum distance value, from the set of vertices # not yet included in shortest path tree def minDistance(self, dist, sptSet): # Initialize minimum distance for next node min = sys.maxsize # Search not nearest vertex not in the # shortest path tree for u in range(self.V): if dist[u] < min and sptSet[u] == False: min = dist[u] min_index = u return min_index # Function that implements Dijkstra's single source # shortest path algorithm for a graph represented # using adjacency matrix representation def dijkstra(self, src): dist = [sys.maxsize] * self.V dist[src] = 0 sptSet = [False] * self.V for cout in range(self.V): # Pick the minimum distance vertex from # the set of vertices not yet processed. # x is always equal to src in first iteration x = self.minDistance(dist, sptSet) # Put the minimum distance vertex in the # shortest path tree sptSet[x] = True # Update dist value of the adjacent vertices # of the picked vertex only if the current # distance is greater than new distance and # the vertex in not in the shortest path tree for y in range(self.V): if self.graph[x][y]>0 および sptSet[y] == False および  dist[y]> dist[x] + self.graph[x][y]: dist[y] = dist[x] + self.graph[x][y] self.printSolution(dist) # ドライバーのコード if __name__ == '__main__': g = Graph(9) g.graph = [[0, 4, 0, 0, 0, 0, 0, 8, 0]、[4、0、8、0、0、0、0、11、0]、[0、8、0、7、0、4、0、0、2]、[0、0、7、 0、9、14、0、0、0]、[0、0、0、9、0、10、0、0、0]、[0、0、4、14、10、0、2、0、 0]、[0、0、0、0、0、2、0、1、6]、[8、11、0、0、0、0、1、0、7]、[0、0、2、 0, 0, 0, 6, 7, 0] ] g.dijkstra(0) # このコードは Divyanshu Mehta によって提供され、Pranav Singh Sambyal によって更新されました>>'C#

// A Javascript program for Dijkstra's single  // source shortest path algorithm.  // The program is for adjacency matrix  // representation of the graph  let V = 9; // A utility function to find the  // vertex with minimum distance  // value, from the set of vertices  // not yet included in shortest  // path tree  function minDistance(dist,sptSet) {    // Initialize min value   let min = Number.MAX_VALUE;  let min_index = -1;    for(let v = 0; v < V; v++)  {  if (sptSet[v] == false && dist[v] <= min)   {  min = dist[v];  min_index = v;  }  }  return min_index; } // A utility function to print  // the constructed distance array  function printSolution(dist) {  console.log('Vertex 		 Distance from Source ');  for(let i = 0; i < V; i++)  {  console.log(i + ' 		 ' +   dist[i] + ' ');  } } // Function that implements Dijkstra's  // single source shortest path algorithm  // for a graph represented using adjacency  // matrix representation  function dijkstra(graph, src) {  let dist = new Array(V);  let sptSet = new Array(V);    // Initialize all distances as   // INFINITE and stpSet[] as false   for(let i = 0; i < V; i++)  {  dist[i] = Number.MAX_VALUE;  sptSet[i] = false;  }    // Distance of source vertex   // from itself is always 0   dist[src] = 0;    // Find shortest path for all vertices   for(let count = 0; count < V - 1; count++)  {    // Pick the minimum distance vertex   // from the set of vertices not yet   // processed. u is always equal to   // src in first iteration.   let u = minDistance(dist, sptSet);    // Mark the picked vertex as processed   sptSet[u] = true;    // Update dist value of the adjacent   // vertices of the picked vertex.   for(let v = 0; v < V; v++)  {    // Update dist[v] only if is not in   // sptSet, there is an edge from u   // to v, and total weight of path   // from src to v through u is smaller   // than current value of dist[v]   if (!sptSet[v] && graph[u][v] != 0 &&   dist[u] != Number.MAX_VALUE &&  dist[u] + graph[u][v] < dist[v])  {  dist[v] = dist[u] + graph[u][v];  }  }  }    // Print the constructed distance array  printSolution(dist); } // Driver code let graph = [ [ 0, 4, 0, 0, 0, 0, 0, 8, 0 ],  [ 4, 0, 8, 0, 0, 0, 0, 11, 0 ],  [ 0, 8, 0, 7, 0, 4, 0, 0, 2 ],  [ 0, 0, 7, 0, 9, 14, 0, 0, 0],  [ 0, 0, 0, 9, 0, 10, 0, 0, 0 ],  [ 0, 0, 4, 14, 10, 0, 2, 0, 0],  [ 0, 0, 0, 0, 0, 2, 0, 1, 6 ],  [ 8, 11, 0, 0, 0, 0, 1, 0, 7 ],  [ 0, 0, 2, 0, 0, 0, 6, 7, 0 ] ] dijkstra(graph, 0); // This code is contributed by rag2127>

// C++ Program to find Dijkstra's shortest path using // priority_queue in STL #include  using namespace std; #define INF 0x3f3f3f3f // iPair ==>整数ペア typedef ペア iペア; // このクラスは、 // 隣接リスト表現を使用して有向グラフを表します。 class Graph { int V; // 頂点の数 // 重み付きグラフでは、すべてのエッジ リストの頂点と // 重みのペアを保存する必要があります>* 形容詞;パブリック: グラフ(int V); // コンストラクター // グラフにエッジを追加する関数 void addEdge(int u, int v, int w);  // s からの最短パスを出力します voidshortPath(int s); }; // 隣接リストにメモリを割り当てます Graph::Graph(int V) { this->V = V;  adj = 新しいリスト [V]; void Graph::addEdge(int u, int v, int w) { adj[u].push_back(make_pair(v, w));  adj[v].push_back(make_pair(u, w)); } // src から他のすべての頂点までの最短パスを出力します void Graph::shortestPath(int src) { // 前処理中の頂点を格納する優先キューを作成します。これは C++ の奇妙な構文です。  // この構文の詳細については、以下のリンクを参照してください // https://www.techcodeview.com priority_queue 、より大きい > pq;  // 距離のベクトルを作成し、 // すべての距離を無限 (INF) ベクトルとして初期化します。 dist(V, INF);  // ソース自体を優先キューに挿入し、 // その距離を 0 として初期化します。 pq.push(make_pair(0, src));  距離[ソース] = 0;  /* 優先キューが空になる (またはすべての距離が確定しない) までループします */ while (!pq.empty()) { // ペアの最初の頂点が最小距離です // 頂点を優先キューから抽出します。  // 頂点ラベルはペアの 2 番目に格納されます ( // 頂点を維持するには、この方法で行う必要があります // ソートされた距離 (距離はペアの // 最初の項目である必要があります) int u = pq.top().second; pq.pop(); // 'i' は頂点リストのすべての隣接する頂点を取得するために使用されます。>::反復子 i;  for (i = adj[u].begin(); i != adj[u].end(); ++i) { // u に隣接する現在の // 頂点ラベルと重みを取得します。  int v = (*i).first;  int 重み = (*i).秒;  // u を介して v へのショートパスがある場合。  if (dist[v]> dist[u] + Weight) { // v の距離を更新 dist[v] = dist[u] + Weight;  pq.push(make_pair(dist[v], v));  } } } // dist[] に格納されている最短距離を出力します printf('ソースからの頂点距離
');  for (int i = 0; i< V; ++i)  printf('%d 		 %d
', i, dist[i]); } // Driver's code int main() {  // create the graph given in above figure  int V = 9;  Graph g(V);  // making above shown graph  g.addEdge(0, 1, 4);  g.addEdge(0, 7, 8);  g.addEdge(1, 2, 8);  g.addEdge(1, 7, 11);  g.addEdge(2, 3, 7);  g.addEdge(2, 8, 2);  g.addEdge(2, 5, 4);  g.addEdge(3, 4, 9);  g.addEdge(3, 5, 14);  g.addEdge(4, 5, 10);  g.addEdge(5, 6, 2);  g.addEdge(6, 7, 1);  g.addEdge(6, 8, 6);  g.addEdge(7, 8, 7);  // Function call  g.shortestPath(0);  return 0; }>

import java.util.*; class Graph {  private int V;  private List> 形容詞;  Graph(int V) { this.V = V;  adj = 新しい ArrayList();  for (int i = 0; i< V; i++) {  adj.add(new ArrayList());  }  }  void addEdge(int u, int v, int w) {  adj.get(u).add(new iPair(v, w));  adj.get(v).add(new iPair(u, w));  }  void shortestPath(int src) {  PriorityQueue pq = new PriorityQueue(V, Comparator.comparingInt(o -> o.second));  int[] dist = 新しい int[V];  Arrays.fill(dist, Integer.MAX_VALUE);  pq.add(new iPair(0, src));  距離[ソース] = 0;  while (!pq.isEmpty()) { int u = pq.poll().second;  for (iPair v : adj.get(u)) { if (dist[v.first]> dist[u] + v.sec) { dist[v.first] = dist[u] + v.sec;  pq.add(new iPair(dist[v.first], v.first));  System.out.println('ソースからの頂点の距離');  for (int i = 0; i< V; i++) {  System.out.println(i + '		' + dist[i]);  }  }  static class iPair {  int first, second;  iPair(int first, int second) {  this.first = first;  this.second = second;  }  } } public class Main {  public static void main(String[] args) {  int V = 9;  Graph g = new Graph(V);  g.addEdge(0, 1, 4);  g.addEdge(0, 7, 8);  g.addEdge(1, 2, 8);  g.addEdge(1, 7, 11);  g.addEdge(2, 3, 7);  g.addEdge(2, 8, 2);  g.addEdge(2, 5, 4);  g.addEdge(3, 4, 9);  g.addEdge(3, 5, 14);  g.addEdge(4, 5, 10);  g.addEdge(5, 6, 2);  g.addEdge(6, 7, 1);  g.addEdge(6, 8, 6);  g.addEdge(7, 8, 7);  g.shortestPath(0);  } }>

import heapq # iPair ==>整数ペア iPair = tuple # このクラスは # 隣接リスト表現クラスを使用して有向グラフを表します Graph: def __init__(self, V: int): # コンストラクター self.V = V self.adj = [[] for _ in range(V )] def addEdge(self, u: int, v: int, w: int): self.adj[u].append((v, w)) self.adj[v].append((u, w)) # src から他のすべての頂点への最短パスを出力します def ShortestPath(self, src: int): # 前処理中の頂点を格納する優先キューを作成します # pq = [] heapq.heappush(pq, (0, src)) #距離のベクトルを作成し、 # すべての距離を無限 (INF) として初期化します dist = [float('inf')] * self.V dist[src] = 0 while pq: # ペアの最初の頂点が最小距離です# 頂点、優先キューから抽出します。 # 頂点ラベルはペア d の 2 番目に格納されます。u = heapq.heappop(pq) # 'i' は、v の頂点の隣接するすべての頂点を取得するために使用されます。# 重みは self.adj[u]: # If u を経由して v へのパスが短縮されています。 if dist[v]> dist[u] + Weight: # v の距離を更新 dist[v] = dist[u] + Weight heapq.heappush(pq, (dist[v], v)) # に格納されている最短距離を出力dist[] for i in range(self.V): print(f'{i} 		 {dist[i]}') # ドライバーのコード if __name__ == '__main__': # 上図のグラフを作成します V = 9 g = Graph(V) # 上図のグラフを作成します g.addEdge(0, 1, 4) g.addEdge(0, 7, 8) g.addEdge(1, 2, 8) g.addEdge(1, 7, 11) g.addEdge(2, 3, 7) g.addEdge(2, 8, 2) g.addEdge(2, 5, 4) g.addEdge(3, 4, 9) g.addEdge(3, 5, 14) g.addEdge(4, 5, 10) g.addEdge(5, 6, 2) g.addEdge(6, 7, 1) g.addEdge(6, 8, 6) g.addEdge(7, 8, 7) g.shortestPath(0)>>C# dist[u] + Weight) { // v の距離を更新 dist[v] = dist[u] + Weight;  pq.Add(new int[] { dist[v], v });  } } } // dist[] に保存されている最短距離を出力します Console.WriteLine('ソースからの頂点距離');  for (int i = 0; i< V; ++i)  Console.WriteLine(i + '	' + dist[i]);  }  private class DistanceComparer : IComparer { public int Compare(int[] x, int[] y) { if (x[0] == y[0]) { return x[1] - y[1];  x[0] - y[0] を返します。  } } } public class Program { // ドライバーコード public static void Main() { // 上図のグラフを作成 int V = 9;  グラフ g = 新しいグラフ(V);  // 上記のグラフを作成します g.AddEdge(0, 1, 4);  g.AddEdge(0, 7, 8);  g.AddEdge(1, 2, 8);  g.AddEdge(1, 7, 11);  g.AddEdge(2, 3, 7);  g.AddEdge(2, 8, 2);  g.AddEdge(2, 5, 4);  g.AddEdge(3, 4, 9);  g.AddEdge(3, 5, 14);  g.AddEdge(4, 5, 10);  g.AddEdge(5, 6, 2);  g.AddEdge(6, 7, 1);  g.AddEdge(6, 8, 6);  g.AddEdge(7, 8, 7);  g.ShortestPath(0);  } } // このコードは bhardwajji によって提供されています>>

// javascript Program to find Dijkstra's shortest path using // priority_queue in STL const INF = 2147483647; // This class represents a directed graph using // adjacency list representation class Graph {    constructor(V){    // No. of vertices  this.V = V;    // In a weighted graph, we need to store vertex  // and weight pair for every edge  this.adj = new Array(V);  for(let i = 0; i < V; i++){  this.adj[i] = new Array();  }  }  addEdge(u, v, w)  {  this.adj[u].push([v, w]);  this.adj[v].push([u, w]);  }  // Prints shortest paths from src to all other vertices  shortestPath(src)  {  // Create a priority queue to store vertices that  // are being preprocessed. This is weird syntax in C++.  // Refer below link for details of this syntax  // https://www.techcodeview.com  let pq = [];  // Create a vector for distances and initialize all  // distances as infinite (INF)  let dist = new Array(V).fill(INF);  // Insert source itself in priority queue and initialize  // its distance as 0.  pq.push([0, src]);  dist[src] = 0;  /* Looping till priority queue becomes empty (or all  distances are not finalized) */  while (pq.length>0) { // ペアの最初の頂点は最小距離です。 // 頂点を優先キューから抽出します。  // 頂点ラベルはペアの 2 番目に格納されます ( // 頂点を維持するにはこの方法で行う必要があります // ソートされた距離 (距離はペアの最初の項目である必要があります // ) let u = pq[0][1]; pq.shift(); // 'i' は、頂点のすべての隣接する頂点を取得するために使用されます。 // for(let i = 0; i< this.adj[u].length; i++){    // Get vertex label and weight of current  // adjacent of u.  let v = this.adj[u][i][0];  let weight = this.adj[u][i][1];  // If there is shorted path to v through u.  if (dist[v]>dist[u] + Weight) { // v の距離を更新 dist[v] = dist[u] + Weight;  pq.push([dist[v], v]);  pq.sort((a, b) =>{ if(a[0] == b[0]) return a[1] - b[1]; return a[0] - b[0]; });  } } } // dist[] に保存されている最短距離を出力します console.log('ソースからの頂点距離');  for (i = 0 とする; i< V; ++i)  console.log(i, ' ', dist[i]);  } } // Driver's code // create the graph given in above figure let V = 9; let g = new Graph(V); // making above shown graph g.addEdge(0, 1, 4); g.addEdge(0, 7, 8); g.addEdge(1, 2, 8); g.addEdge(1, 7, 11); g.addEdge(2, 3, 7); g.addEdge(2, 8, 2); g.addEdge(2, 5, 4); g.addEdge(3, 4, 9); g.addEdge(3, 5, 14); g.addEdge(4, 5, 10); g.addEdge(5, 6, 2); g.addEdge(6, 7, 1); g.addEdge(6, 8, 6); g.addEdge(7, 8, 7); // Function call g.shortestPath(0); // The code is contributed by Nidhi goel.>