Dijkstra's Algorithm is a greedy algorithm used to find the shortest path from a single source node to all other nodes in a weighted graph with non-negative weights. We can adapt it to efficiently find the shortest path for this problem.
Time Complexity: O(V^2), where V is the number of vertices since we're using an adjacency matrix and no priority queue to obtain the minimum distance vertex.
Space Complexity: O(V^2) due to the adjacency matrix storage requirements.
1class Graph {
2 constructor(n, edges) {
3 this.n = n;
4 this.adj = Array.from({ length: n }, () => []);
5 for (const [u, v, cost] of edges) {
6 this.adj[u].push([v, cost]);
7 }
8 }
9
10 addEdge(edge) {
11 const [u, v, cost] = edge;
12 this.adj[u].push([v, cost]);
13 }
14
15 shortestPath(node1, node2) {
16 const dist = new Array(this.n).fill(Infinity);
17 dist[node1] = 0;
18 const pq = new PriorityQueue((a, b) => a[0] < b[0]);
19 pq.enqueue([0, node1]);
20
21 while (!pq.isEmpty()) {
22 const [curDist, u] = pq.dequeue();
23 if (u === node2) return curDist;
24 if (curDist > dist[u]) continue;
25
26 for (const [v, cost] of this.adj[u]) {
27 if (dist[u] + cost < dist[v]) {
28 dist[v] = dist[u] + cost;
29 pq.enqueue([dist[v], v]);
30 }
31 }
32 }
33 return -1;
34 }
35}
36
37class PriorityQueue {
38 constructor(comparator) {
39 this.data = [];
40 this.comparator = comparator;
41 }
42
43 enqueue(value) {
44 this.data.push(value);
45 this.data.sort(this.comparator);
46 }
47
48 dequeue() {
49 return this.data.shift();
50 }
51
52 isEmpty() {
53 return this.data.length === 0;
54 }
55}
56
57// Demonstration
58const edges = [[0, 2, 5], [0, 1, 2], [1, 2, 1], [3, 0, 3]];
59const graph = new Graph(4, edges);
60console.log(graph.shortestPath(3, 2)); // Output: 6
61console.log(graph.shortestPath(0, 3)); // Output: -1
62graph.addEdge([1, 3, 4]);
63console.log(graph.shortestPath(0, 3)); // Output: 6
64
JavaScript utilizes a simple priority queue implementation to keep track of and process nodes by minimized distances while computing shortest paths.
The Floyd-Warshall Algorithm is a dynamic programming algorithm used to find shortest paths between all pairs of vertices in a weighted graph. This approach is more suited when there are frequent shortest path queries between multiple different node pairs.
Time Complexity: O(n^3), where n is the number of vertices, arising from the three nested loops.
Space Complexity: O(n^2) due to the distance matrix storage covering all node pairs.
1#include <stdio.h>
2#include <stdlib.h>
3#include <limits.h>
4
5#define INF INT_MAX
6
7typedef struct {
8 int n;
9 int** dist;
10} Graph;
11
12Graph* createGraph(int n, int edges[][3], int edgesSize) {
13 Graph* graph = (Graph*)malloc(sizeof(Graph));
14 graph->n = n;
15 graph->dist = (int**)malloc(n * sizeof(int*));
16 for (int i = 0; i < n; i++) {
17 graph->dist[i] = (int*)malloc(n * sizeof(int));
18 for (int j = 0; j < n; j++)
19 graph->dist[i][j] = (i == j) ? 0 : INF;
20 }
21 for (int i = 0; i < edgesSize; i++) {
22 int u = edges[i][0];
23 int v = edges[i][1];
24 graph->dist[u][v] = edges[i][2];
25 }
26 for (int k = 0; k < n; k++) {
27 for (int i = 0; i < n; i++) {
28 for (int j = 0; j < n; j++) {
29 if (graph->dist[i][k] != INF && graph->dist[k][j] != INF)
30 graph->dist[i][j] = (graph->dist[i][j] > graph->dist[i][k] + graph->dist[k][j]) ? graph->dist[i][k] + graph->dist[k][j] : graph->dist[i][j];
31 }
32 }
33 }
34
35 return graph;
36}
37
38void addEdge(Graph* graph, int u, int v, int cost) {
39 graph->dist[u][v] = cost;
40 // Re-run Floyd-Warshall
41 for (int k = 0; k < graph->n; k++) {
42 for (int i = 0; i < graph->n; i++) {
43 for (int j = 0; j < graph->n; j++) {
44 if (graph->dist[i][k] != INF && graph->dist[k][j] != INF)
45 graph->dist[i][j] = (graph->dist[i][j] > graph->dist[i][k] + graph->dist[k][j]) ? graph->dist[i][k] + graph->dist[k][j] : graph->dist[i][j];
46 }
47 }
48 }
49}
50
51int shortestPath(Graph* graph, int node1, int node2) {
52 if(graph->dist[node1][node2] == INF)
53 return -1;
54 return graph->dist[node1][node2];
55}
56
57int main() {
58 int edges[4][3] = {{0, 2, 5}, {0, 1, 2}, {1, 2, 1}, {3, 0, 3}};
59 Graph* graph = createGraph(4, edges, 4);
60 printf("%d\n", shortestPath(graph, 3, 2)); // Output: 6
61 printf("%d\n", shortestPath(graph, 0, 3)); // Output: -1
62 addEdge(graph, 1, 3, 4);
63 printf("%d\n", shortestPath(graph, 0, 3)); // Output: 6
64
65 // Free the memory
66 for(int i = 0; i < graph->n; i++)
67 free(graph->dist[i]);
68 free(graph->dist);
69 free(graph);
70 return 0;
71}
This implementation uses Floyd-Warshall Algorithm, which precomputes shortest paths between all pairs of nodes. Post addEdge operations, the algorithm recomputes paths by potentially updating the distance matrix.