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154 changes: 154 additions & 0 deletions CPP/algorithms/graph_algorithms/dijkstra_algorithm.cpp
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// Dijkstra’s Algorithm — Single Source Shortest Path
// Problem
// Given a weighted graph with non-negative edge weights,
// find the shortest path from a source vertex to all other vertices.
//
// Approach
// 1. Use a priority queue (min-heap) to always expand the next closest vertex.
// 2. Initialize distances[] with infinity, except source = 0.
// 3. While queue not empty:
// - Extract vertex u with smallest dist[u].
// - For each neighbor v of u, relax edge (u,v):
// if dist[u] + weight(u,v) < dist[v], update dist[v].
//
// Complexity
// Time : O((V + E) log V) — using priority queue
// Space : O(V + E) — adjacency list + distance array + heap
//
// Input
// - Number of vertices (V)
// - Number of edges (E)
// - Edge list {u, v, w} (u → v with weight w)
// - Source vertex (src)
//
// Output
// - Shortest distance from src to all vertices

#include <iostream>
#include <vector>
#include <queue>
#include <limits>
using namespace std;

int main()
{
ios::sync_with_stdio(false);
cin.tie(nullptr);

int V, E;
cin >> V >> E;
vector<vector<pair<int, int>>> adj(V);

for (int i = 0; i < E; i++)
{
int u, v, w;
cin >> u >> v >> w;
adj[u].push_back({v, w});
adj[v].push_back({u, w}); // undirected; remove if directed
}

int src;
cin >> src;

const int INF = numeric_limits<int>::max();
vector<int> dist(V, INF);
dist[src] = 0;

// min-heap {distance, vertex}
priority_queue<pair<int, int>, vector<pair<int, int>>, greater<>> pq;
pq.push({0, src});

while (!pq.empty())
{
int d = pq.top().first;
int u = pq.top().second;
pq.pop();
if (d > dist[u])
continue; // outdated entry

for (auto &edge : adj[u])
{
int v = edge.first, w = edge.second;
if (dist[u] + w < dist[v])
{
dist[v] = dist[u] + w;
pq.push({dist[v], v});
}
}
}

cout << "Shortest distances from source " << src << ":\n";
for (int i = 0; i < V; i++)
{
if (dist[i] == INF)
cout << i << " : INF\n";
else
cout << i << " : " << dist[i] << "\n";
}

return 0;
}

/*
Example Input:
5 6
0 1 2
0 2 4
1 2 1
1 3 7
2 4 3
3 4 1
0

Visualization:
Graph:
(2)
0 ------- 1
\ / \
(4)\ (1) (7)
\ / \
2 ------- 3
\ /
(3) (1)
\ /
4

Execution:
dist = [0, INF, INF, INF, INF]
Start from src=0

Step 1: Pick 0 → dist[0]=0
Relax edges:
0→1 (2) → dist[1]=2
0→2 (4) → dist[2]=4
dist = [0,2,4,INF,INF]

Step 2: Pick 1 (dist=2)
Relax edges:
1→2 (1) → dist[2]=min(4,2+1)=3
1→3 (7) → dist[3]=2+7=9
dist = [0,2,3,9,INF]

Step 3: Pick 2 (dist=3)
Relax edges:
2→4 (3) → dist[4]=3+3=6
dist = [0,2,3,9,6]

Step 4: Pick 4 (dist=6) → relax 4→3 (1):
dist[3]=min(9,6+1)=7
dist = [0,2,3,7,6]

Step 5: Pick 3 (dist=7) → no better updates

Final distances from 0:
0 : 0
1 : 2
2 : 3
3 : 7
4 : 6

Time : O((V+E) log V)
Space : O(V+E)
*/

// add: Dijkstra PR