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.
1using System;
2using System.Collections.Generic;
3
4public class Graph {
5 private int n;
6 private List<List<(int, int)>> adj;
7
8 public Graph(int n, int[][] edges) {
9 this.n = n;
10 this.adj = new List<List<(int, int)>>();
11 for (int i = 0; i < n; i++) {
12 adj.Add(new List<(int, int)>());
13 }
14 foreach (var edge in edges) {
15 adj[edge[0]].Add((edge[1], edge[2]));
16 }
17 }
18
19 public void AddEdge(int[] edge) {
20 adj[edge[0]].Add((edge[1], edge[2]));
21 }
22
23 public int ShortestPath(int node1, int node2) {
24 int[] dist = new int[n];
25 Array.Fill(dist, int.MaxValue);
26 dist[node1] = 0;
27
28 var pq = new SortedSet<(int Distance, int Vertex)>(Comparer<(int, int)>.Create((x, y) => {
29 int result = x.Distance.CompareTo(y.Distance);
30 return result == 0 ? x.Vertex.CompareTo(y.Vertex) : result;
31 }));
32 pq.Add((0, node1));
33
34 while (pq.Count > 0) {
35 var current = pq.Min;
36 pq.Remove(current);
37 int u = current.Vertex;
38 int curDist = current.Distance;
39
40 if (u == node2) return curDist;
41 if (curDist > dist[u]) continue;
42
43 foreach (var (v, cost) in adj[u]) {
44 if (dist[u] + cost < dist[v]) {
45 dist[v] = dist[u] + cost;
46 pq.Add((dist[v], v));
47 }
48 }
49 }
50 return -1;
51 }
52
53 public static void Main() {
54 int[][] edges = new int[][] { new int[] { 0, 2, 5 }, new int[] { 0, 1, 2 }, new int[] { 1, 2, 1 }, new int[] { 3, 0, 3 } };
55 Graph g = new Graph(4, edges);
56 Console.WriteLine(g.ShortestPath(3, 2)); // Output: 6
57 Console.WriteLine(g.ShortestPath(0, 3)); // Output: -1
58 g.AddEdge(new int[] { 1, 3, 4 });
59 Console.WriteLine(g.ShortestPath(0, 3)); // Output: 6
60 }
61}
The C# implementation leverages a `SortedSet` for prioritizing graph nodes based on their cumulative path distance, thereby optimizing time complexity when executing Dijkstra's shortest path algorithm.
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.
1import java.util.*;
2
3class Graph {
4 private int n;
5 private int[][] dist;
6
7 public Graph(int n, int[][] edges) {
8 this.n = n;
9 dist = new int[n][n];
10 for (int[] row : dist)
11 Arrays.fill(row, Integer.MAX_VALUE);
12 for (int i = 0; i < n; i++)
13 dist[i][i] = 0;
14 for (int[] edge : edges) {
15 dist[edge[0]][edge[1]] = edge[2];
16 }
17 floydWarshall();
18 }
19
20 public void floydWarshall() {
21 for (int k = 0; k < n; k++) {
22 for (int i = 0; i < n; i++) {
23 for (int j = 0; j < n; j++) {
24 if (dist[i][k] != Integer.MAX_VALUE && dist[k][j] != Integer.MAX_VALUE)
25 dist[i][j] = Math.min(dist[i][j], dist[i][k] + dist[k][j]);
26 }
27 }
28 }
29 }
30
31 public void addEdge(int[] edge) {
32 dist[edge[0]][edge[1]] = edge[2];
33 floydWarshall();
34 }
35
36 public int shortestPath(int node1, int node2) {
37 return dist[node1][node2] == Integer.MAX_VALUE ? -1 : dist[node1][node2];
38 }
39
40 public static void main(String[] args) {
41 int[][] edges = {{0, 2, 5}, {0, 1, 2}, {1, 2, 1}, {3, 0, 3}};
42 Graph graph = new Graph(4, edges);
43 System.out.println(graph.shortestPath(3, 2)); // Output: 6
44 System.out.println(graph.shortestPath(0, 3)); // Output: -1
45 graph.addEdge(new int[]{1, 3, 4});
46 System.out.println(graph.shortestPath(0, 3)); // Output: 6
47 }
48}
Java implements Floyd-Warshall to precompute path efficiencies across the graph's entirety, recalculating these values upon any edge addition to account for potential novel shortest routes.