// 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 a sptSet[y] == False a  dist[y]> dist[x] + self.graph[x][y]: dist[y] = dist[x] + self.graph[x][y] self.printSolution(dist) # Kód vodiča, ak __name__ == '__main__': g = Graf(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) # Tento kód prispel Divyanshu Mehta a aktualizoval Pranav Singh Sambyal>

// C# program for Dijkstra's single // source shortest path algorithm. // The program is for adjacency matrix // representation of the graph using System; class GFG {  // A utility function to find the  // vertex with minimum distance  // value, from the set of vertices  // not yet included in shortest  // path tree  static int V = 9;  int minDistance(int[] dist, bool[] sptSet)  {  // Initialize min value  int min = int.MaxValue, 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)  {  Console.Write('Vertex 		 Distance '  + 'from Source
');  for (int i = 0; i < V; i++)  Console.Write(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  bool[] sptSet = new bool[V];  // Initialize all distances as  // INFINITE and stpSet[] as false  for (int i = 0; i < V; i++) {  dist[i] = int.MaxValue;  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] != int.MaxValue  && 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()  {  /* 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 } };  GFG t = new GFG();  // Function call  t.dijkstra(graph, 0);  } } // This code is contributed by ChitraNayal>

// 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 ==>Integer Pair typedef pair iPair; // Táto trieda predstavuje orientovaný graf pomocou // triedy reprezentácie zoznamu susediacich Graph { int V; // Počet vrcholov // Vo váženom grafe musíme uložiť vrchol // a pár váh pre každý zoznam hrán>* adj; verejné: Graf(int V); // Konštruktor // funkcia na pridanie hrany do grafu void addEdge(int u, int v, int w);  // vypíše najkratšiu cestu z s void shortestPath(int s); }; // Alokuje pamäť pre zoznam susediacich Graph::Graph(int V) { this->V = V;  adj = nový zoznam [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)); } // Vypíše najkratšie cesty z src do všetkých ostatných vrcholov void Graph::shortestPath(int src) { // Vytvorenie prioritného frontu na ukladanie vrcholov, ktoré // sa predspracujú. Toto je zvláštna syntax v C++.  // Podrobnosti o tejto syntaxi nájdete na nižšie uvedenom odkaze // https://www.techcodeview.com priority_queue , väčší > pq;  // Vytvorte vektor pre vzdialenosti a inicializujte všetky // vzdialenosti ako nekonečný (INF) vektor dist(V, INF);  // Vložte samotný zdroj do prioritného frontu a inicializujte // jeho vzdialenosť ako 0. pq.push(make_pair(0, src));  dist[src] = 0;  /* Opakuje sa, kým sa prioritný front nevyprázdni (alebo všetky vzdialenosti nie sú dokončené) */ while (!pq.empty()) { // Prvý vrchol v páre je minimálna vzdialenosť // vrchol, extrahujte ho z prioritného frontu.  // označenie vrcholu je uložené v sekunde z páru (musí sa to urobiť // týmto spôsobom, aby sa zachovali vrcholy // zoradená vzdialenosť (vzdialenosť musí byť prvá položka // v páre) int u = pq.top().second; pq.pop(); // 'i' sa používa na získanie všetkých susedných vrcholov // zoznamu vrcholov>::iterátor i;  for (i = adj[u].begin(); i != adj[u].end(); ++i) { // Získanie označenia vrcholu a váhy aktuálneho // susediaceho s u.  int v = (*i).prvý;  int váha = (*i).sekunda;  // Ak existuje skrátená cesta k v cez u.  if (dist[v]> dist[u] + hmotnosť) { // Aktualizácia vzdialenosti v dist[v] = dist[u] + hmotnosť;  pq.push(make_pair(dist[v], v));  } } } // Tlač najkratších vzdialeností uložených v dist[] printf('Vzdialenosť vrcholu od zdroja
');  pre (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> adj;  Graph(int V) { this.V = V;  adj = new ArrayList();  pre (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 = nový int[V];  Arrays.fill(dist, Integer.MAX_VALUE);  pq.add(new iPair(0, src));  dist[src] = 0;  while (!pq.isEmpty()) { int u = pq.poll().second;  for (iPair v : adj.get(u)) { if (dist[v.first]> dist[u] + v.second) { dist[v.first] = dist[u] + v.second;  pq.add(new iPair(dist[v.first], v.first));  } } } System.out.println('Vzdialenosť vrcholu od zdroja');  pre (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 ==>Celočíselný pár iPair = n-tica # Táto trieda predstavuje orientovaný graf pomocou # triedy reprezentácie zoznamu susednosti Graf: def __init__(self, V: int): # Konštruktor 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)) # Vytlačí najkratšie cesty z src do všetkých ostatných vrcholov def shortestPath(self, src: int): # Vytvorte prioritný front na uloženie vrcholov, ktoré # sa predspracujú pq = [] heapq.heappush(pq, (0, src)) # Vytvorte vektor pre vzdialenosti a inicializujte všetky # vzdialenosti ako nekonečné (INF) dist = [float('inf')] * self.V dist[src] = 0 pričom pq: # Prvý vrchol v páre je minimálna vzdialenosť # vertex, extrahujte ho z prioritného frontu. # vertex label je uložený v sekunde páru d, u = heapq.heappop(pq) # 'i' sa používa na získanie všetkých susedných vrcholov # vrcholu pre v, váhu v self.adj[u]: # If je tam skrátená cesta do v cez u. if dist[v]> dist[u] + hmotnosť: # Aktualizácia vzdialenosti v dist[v] = dist[u] + hmotnosť heapq.heappush(pq, (dist[v], v)) # Tlačiť najkratšie vzdialenosti uložené v dist[] for i in range(self.V): print(f'{i} 		 {dist[i]}') # Kód vodiča, ak __name__ == '__main__': # vytvorte graf uvedený na obrázku vyššie V = 9 g = Graph(V) # vytvorte vyššie uvedený graf 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)>

using System; using System.Collections.Generic; // This class represents a directed graph using // adjacency list representation public class Graph {  private const int INF = 2147483647;  private int V;  private List [] adj;  public Graf(int V) { // Počet vrcholov this.V = V;  // Vo váženom grafe musíme uložiť vrchol // a pár váh pre každú hranu this.adj = new List [V];  pre (int i = 0; i< V; i++)  {  this.adj[i] = new List ();  } } public void AddEdge(int u, int v, int w) { this.adj[u].Add(new int[] { v, w });  this.adj[v].Add(new int[] { u, w });  } // Vypíše najkratšie cesty z src do všetkých ostatných vrcholov public void ShortestPath(int src) { // Vytvorenie prioritného frontu na ukladanie vrcholov, ktoré // sú predspracované.  SortedSet pq = new SortedSet (nový DistanceComparer());  // Vytvorte pole pre vzdialenosti a inicializujte všetky // vzdialenosti ako nekonečné (INF) int[] dist = new int[V];  pre (int i = 0; i< V; i++)  {  dist[i] = INF;  }  // Insert source itself in priority queue and initialize  // its distance as 0.  pq.Add(new int[] { 0, src });  dist[src] = 0;  /* Looping till priority queue becomes empty (or all  distances are not finalized) */  while (pq.Count>0) { // Prvý vrchol v páre je minimálna vzdialenosť // vrchol, extrahujte ho z prioritného frontu.  // štítok vrcholu je uložený v sekunde z páru (// treba to urobiť týmto spôsobom, aby sa vrcholy // zoradili podľa vzdialenosti) int[] minDistVertex = pq.Min;  pq.Remove(minDistVertex);  int u = minDistVertex[1];  // 'i' sa používa na získanie všetkých susedných vrcholov // vrcholu foreach (int[] adjVertex v tomto.adj[u]) { // Získanie označenia vrcholu a váhy aktuálneho // susediaceho s u.  int v = adjVertex[0];  int váha = adjVertex[1];  // Ak existuje kratšia cesta k v cez u.  if (dist[v]> dist[u] + hmotnosť) { // Aktualizácia vzdialenosti v dist[v] = dist[u] + hmotnosť;  pq.Add(new int[] { dist[v], v });  } } } // Tlač najkratších vzdialeností uložených v dist[] Console.WriteLine('Vzdialenosť vrcholu od zdroja');  pre (int i = 0; i< V; ++i)  Console.WriteLine(i + '	' + dist[i]);  }  private class DistanceComparer : IComparer { public int Porovnaj(int[] x, int[] y) { if (x[0] == y[0]) { return x[1] - y[1];  } return x[0] - y[0];  } } } public class Program { // Kód ovládača public static void Main() { // vytvorte graf uvedený na obrázku vyššie int V = 9;  Graph g = new Graph(V);  // vytvorenie vyššie uvedeného grafu 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);  } } // tento kód prispel bhardwajji>

// 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) { // Prvý vrchol v páre je minimálna vzdialenosť // vrchol, extrahujte ho z prioritného frontu.  // štítok vrcholu je uložený v druhom z páru (to // treba urobiť týmto spôsobom, aby sa zachovali vrcholy // zoradená vzdialenosť (vzdialenosť musí byť prvá položka // v páre) nech u = pq[0][1]; pq.shift() // 'i' sa používa na získanie všetkých susedných vrcholov // vrcholu for(nech 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] + hmotnosť) { // Aktualizácia vzdialenosti v dist[v] = dist[u] + hmotnosť;  pq.push([dist[v], v]);  pq.sort((a, b) =>{ if(a[0] == b[0]) return a[1] - b[1]; return a[0] - b[0]; });  } } } // Tlač najkratších vzdialeností uložených v dist[] console.log('Vzdialenosť vrcholu od zdroja');  pre (nech i = 0; 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.>