dijkstra’s algorithm java code example

Example 1: java djikstra's algorithm

import java.util.*; 
public class DPQ { 
    private int dist[]; 
    private Set<Integer> settled; 
    private PriorityQueue<Node> pq; 
    private int V; // Number of vertices 
    List<List<Node> > adj; 
  
    public DPQ(int V) 
    { 
        this.V = V; 
        dist = new int[V]; 
        settled = new HashSet<Integer>(); 
        pq = new PriorityQueue<Node>(V, new Node()); 
    } 
  
    // Function for Dijkstra's Algorithm 
    public void dijkstra(List<List<Node> > adj, int src) 
    { 
        this.adj = adj; 
  
        for (int i = 0; i < V; i++) 
            dist[i] = Integer.MAX_VALUE; 
  
        // Add source node to the priority queue 
        pq.add(new Node(src, 0)); 
  
        // Distance to the source is 0 
        dist[src] = 0; 
        while (settled.size() != V) { 
  
            // remove the minimum distance node  
            // from the priority queue  
            int u = pq.remove().node; 
  
            // adding the node whose distance is 
            // finalized 
            settled.add(u); 
  
            e_Neighbours(u); 
        } 
    } 
  
    // Function to process all the neighbours  
    // of the passed node 
    private void e_Neighbours(int u) 
    { 
        int edgeDistance = -1; 
        int newDistance = -1; 
  
        // All the neighbors of v 
        for (int i = 0; i < adj.get(u).size(); i++) { 
            Node v = adj.get(u).get(i); 
  
            // If current node hasn't already been processed 
            if (!settled.contains(v.node)) { 
                edgeDistance = v.cost; 
                newDistance = dist[u] + edgeDistance; 
  
                // If new distance is cheaper in cost 
                if (newDistance < dist[v.node]) 
                    dist[v.node] = newDistance; 
  
                // Add the current node to the queue 
                pq.add(new Node(v.node, dist[v.node])); 
            } 
        } 
    } 
  
    // Driver code 
    public static void main(String arg[]) 
    { 
        int V = 5; 
        int source = 0; 
  
        // Adjacency list representation of the  
        // connected edges 
        List<List<Node> > adj = new ArrayList<List<Node> >(); 
  
        // Initialize list for every node 
        for (int i = 0; i < V; i++) { 
            List<Node> item = new ArrayList<Node>(); 
            adj.add(item); 
        } 
  
        // Inputs for the DPQ graph 
        adj.get(0).add(new Node(1, 9)); 
        adj.get(0).add(new Node(2, 6)); 
        adj.get(0).add(new Node(3, 5)); 
        adj.get(0).add(new Node(4, 3)); 
  
        adj.get(2).add(new Node(1, 2)); 
        adj.get(2).add(new Node(3, 4)); 
  
        // Calculate the single source shortest path 
        DPQ dpq = new DPQ(V); 
        dpq.dijkstra(adj, source); 
  
        // Print the shortest path to all the nodes 
        // from the source node 
        System.out.println("The shorted path from node :"); 
        for (int i = 0; i < dpq.dist.length; i++) 
            System.out.println(source + " to " + i + " is "
                               + dpq.dist[i]); 
    } 
} 
  
// Class to represent a node in the graph 
class Node implements Comparator<Node> { 
    public int node; 
    public int cost; 
  
    public Node() 
    { 
    } 
  
    public Node(int node, int cost) 
    { 
        this.node = node; 
        this.cost = cost; 
    } 
  
    @Override
    public int compare(Node node1, Node node2) 
    { 
        if (node1.cost < node2.cost) 
            return -1; 
        if (node1.cost > node2.cost) 
            return 1; 
        return 0; 
    } 
}

Example 2: dijkstra algorithm

//djikstra's algorithm using a weighted graph (STL)
//code by Soumyadepp
//insta: @soumyadepp
//linkedinID: https://www.linkedin.com/in/soumyadeep-ghosh-90a1951b6/

#include <bits/stdc++.h>
#define ll long long
using namespace std;

//to find the closest unvisited vertex from the source
//note that numbering of vertices starts from 1 here. Calculate accordingly
ll minDist(ll dist[], ll n, bool visited[])
{
    ll min = INT_MAX;
    ll minIndex = 0;
    for (ll i = 1; i <= n; i++)
    {
        if (!visited[i] && dist[i] <= min)
        {
            min = dist[i];
            minIndex = i;
        }
    }
    return minIndex;
}

//djikstra's algorithm for single source shortest path
void djikstra(vector<pair<ll, ll>> *g, ll n, ll src)
{
    bool visited[n + 1];
    ll dist[n + 1];
    for (ll i = 0; i <= n; i++)
    {
        dist[i] = INT_MAX;
        visited[i] = false;
    }

    dist[src] = 0;

    for (ll i = 0; i < n - 1; i++)
    {
        ll u = minDist(dist, n, visited);
        visited[u] = true;
        for (ll v = 0; v < g[u].size(); v++)
        {
            if (dist[u] + g[u][v].second < dist[g[u][v].first])
            {
                dist[g[u][v].first] = dist[u] + g[u][v].second;
            }
        }
    }
    cout << "VERTEX : DISTANCE" << endl;
    for (ll i = 1; i <= n; i++)
    {
        if (dist[i] != INT_MAX)
            cout << i << "         " << dist[i] << endl;
        else
            cout << i << "         "
                 << "not reachable" << endl;
    }
    cout << endl;
}

int main()
{
    //to store the adjacency list which also contains the weight
    vector<pair<ll, ll>> *graph;
    ll n, e, x, y, w, src;
    cout << "Enter number of vertices and edges in the graph" << endl;
    cin >> n >> e;
    graph = new vector<pair<ll, ll>>[n + 1];
    cout << "Enter edges and weight" << endl;
    for (ll i = 0; i < e; i++)
    {
        cin >> x >> y >> w;
        //checking for invalid edges and negative weights.
        if (x <= 0 || y <= 0 || w <= 0)
        {
            cout << "Invalid parameters. Exiting" << endl;
            exit(-1);
        }
        graph[x].push_back(make_pair(y, w));
        graph[y].push_back(make_pair(x, w));
    }
    cout << "Enter source from which you want to find shortest paths" << endl;
    cin >> src;
    if (src >= 1 && src <= n)
        djikstra(graph, n, src);
    else
        cout << "Please enter a valid vertex as the source" << endl;
    return 0;
}

//time complexity : O(ElogV)
//space complexity: O(V)

Example 3: dijkstra's algorithm

# Providing the graph
n = int(input("Enter the number of vertices of the graph"))

# using adjacency matrix representation 
vertices = [[0, 0, 1, 1, 0, 0, 0],
            [0, 0, 1, 0, 0, 1, 0],
            [1, 1, 0, 1, 1, 0, 0],
            [1, 0, 1, 0, 0, 0, 1],
            [0, 0, 1, 0, 0, 1, 0],
            [0, 1, 0, 0, 1, 0, 1],
            [0, 0, 0, 1, 0, 1, 0]]

edges = [[0, 0, 1, 2, 0, 0, 0],
         [0, 0, 2, 0, 0, 3, 0],
         [1, 2, 0, 1, 3, 0, 0],
         [2, 0, 1, 0, 0, 0, 1],
         [0, 0, 3, 0, 0, 2, 0],
         [0, 3, 0, 0, 2, 0, 1],
         [0, 0, 0, 1, 0, 1, 0]]

# Find which vertex is to be visited next
def to_be_visited():
    global visited_and_distance
    v = -10
    for index in range(num_of_vertices):
        if visited_and_distance[index][0] == 0 \
            and (v < 0 or visited_and_distance[index][1] <=
                 visited_and_distance[v][1]):
            v = index
    return v


num_of_vertices = len(vertices[0])

visited_and_distance = [[0, 0]]
for i in range(num_of_vertices-1):
    visited_and_distance.append([0, sys.maxsize])

for vertex in range(num_of_vertices):

    # Find next vertex to be visited
    to_visit = to_be_visited()
    for neighbor_index in range(num_of_vertices):

        # Updating new distances
        if vertices[to_visit][neighbor_index] == 1 and 
                visited_and_distance[neighbor_index][0] == 0:
            new_distance = visited_and_distance[to_visit][1] 
                + edges[to_visit][neighbor_index]
            if visited_and_distance[neighbor_index][1] > new_distance:
                visited_and_distance[neighbor_index][1] = new_distance
        
        visited_and_distance[to_visit][0] = 1

i = 0

# Printing the distance
for distance in visited_and_distance:
    print("Distance of ", chr(ord('a') + i),
          " from source vertex: ", distance[1])
    i = i + 1