Kruskal's algorithm is a minimum spanning tree algorithm that takes a graph as input and finds the subset of the edges of that graph which
- form a tree that includes every vertex
- has the minimum sum of weights among all the trees that can be formed from the graph
We start from the edges with the lowest weight and keep adding edges until we reach our goal.
The steps for implementing Kruskal's algorithm are as follows:
- Sort all the edges from low weight to high
- Take the edge with the lowest weight and add it to the spanning tree. If adding the edge created a cycle, then reject this edge.
- Keep adding edges until we reach all vertices.
The time complexity Of Kruskal's Algorithm is: O(E log E).
KRUSKAL(G):
A = ∅
For each vertex v ∈ G.V:
MAKE-SET(v)
For each edge (u, v) ∈ G.E ordered by increasing order by weight(u, v):
if FIND-SET(u) ≠ FIND-SET(v):
A = A ∪ {(u, v)}
UNION(u, v)
return A
// Kruskal's algorithm in C++
#include <algorithm>
#include <iostream>
#include <vector>
using namespace std;
#define edge pair<int, int>
class Graph {
private:
vector<pair<int, edge> > G; // graph
vector<pair<int, edge> > T; // mst
int *parent;
int V; // number of vertices/nodes in graph
public:
Graph(int V);
void AddWeightedEdge(int u, int v, int w);
int find_set(int i);
void union_set(int u, int v);
void kruskal();
void print();
};
Graph::Graph(int V) {
parent = new int[V];
//i 0 1 2 3 4 5
//parent[i] 0 1 2 3 4 5
for (int i = 0; i < V; i++)
parent[i] = i;
G.clear();
T.clear();
}
void Graph::AddWeightedEdge(int u, int v, int w) {
G.push_back(make_pair(w, edge(u, v)));
}
int Graph::find_set(int i) {
// If i is the parent of itself
if (i == parent[i])
return i;
else
// Else if i is not the parent of itself
// Then i is not the representative of his set,
// so we recursively call Find on its parent
return find_set(parent[i]);
}
void Graph::union_set(int u, int v) {
parent[u] = parent[v];
}
void Graph::kruskal() {
int i, uRep, vRep;
sort(G.begin(), G.end()); // increasing weight
for (i = 0; i < G.size(); i++) {
uRep = find_set(G[i].second.first);
vRep = find_set(G[i].second.second);
if (uRep != vRep) {
T.push_back(G[i]); // add to tree
union_set(uRep, vRep);
}
}
}
void Graph::print() {
cout << "Edge :"
<< " Weight" << endl;
for (int i = 0; i < T.size(); i++) {
cout << T[i].second.first << " - " << T[i].second.second << " : "
<< T[i].first;
cout << endl;
}
}
int main() {
Graph g(6);
g.AddWeightedEdge(0, 1, 4);
g.AddWeightedEdge(0, 2, 4);
g.AddWeightedEdge(1, 2, 2);
g.AddWeightedEdge(1, 0, 4);
g.AddWeightedEdge(2, 0, 4);
g.AddWeightedEdge(2, 1, 2);
g.AddWeightedEdge(2, 3, 3);
g.AddWeightedEdge(2, 5, 2);
g.AddWeightedEdge(2, 4, 4);
g.AddWeightedEdge(3, 2, 3);
g.AddWeightedEdge(3, 4, 3);
g.AddWeightedEdge(4, 2, 4);
g.AddWeightedEdge(4, 3, 3);
g.AddWeightedEdge(5, 2, 2);
g.AddWeightedEdge(5, 4, 3);
g.kruskal();
g.print();
return 0;
}// Kruskal's algorithm in C
#include <stdio.h>
#define MAX 30
typedef struct edge {
int u, v, w;
} edge;
typedef struct edge_list {
edge data[MAX];
int n;
} edge_list;
edge_list elist;
int Graph[MAX][MAX], n;
edge_list spanlist;
void kruskalAlgo();
int find(int belongs[], int vertexno);
void applyUnion(int belongs[], int c1, int c2);
void sort();
void print();
// Applying Krushkal Algo
void kruskalAlgo() {
int belongs[MAX], i, j, cno1, cno2;
elist.n = 0;
for (i = 1; i < n; i++)
for (j = 0; j < i; j++) {
if (Graph[i][j] != 0) {
elist.data[elist.n].u = i;
elist.data[elist.n].v = j;
elist.data[elist.n].w = Graph[i][j];
elist.n++;
}
}
sort();
for (i = 0; i < n; i++)
belongs[i] = i;
spanlist.n = 0;
for (i = 0; i < elist.n; i++) {
cno1 = find(belongs, elist.data[i].u);
cno2 = find(belongs, elist.data[i].v);
if (cno1 != cno2) {
spanlist.data[spanlist.n] = elist.data[i];
spanlist.n = spanlist.n + 1;
applyUnion(belongs, cno1, cno2);
}
}
}
int find(int belongs[], int vertexno) {
return (belongs[vertexno]);
}
void applyUnion(int belongs[], int c1, int c2) {
int i;
for (i = 0; i < n; i++)
if (belongs[i] == c2)
belongs[i] = c1;
}
// Sorting algo
void sort() {
int i, j;
edge temp;
for (i = 1; i < elist.n; i++)
for (j = 0; j < elist.n - 1; j++)
if (elist.data[j].w > elist.data[j + 1].w) {
temp = elist.data[j];
elist.data[j] = elist.data[j + 1];
elist.data[j + 1] = temp;
}
}
// Printing the result
void print() {
int i, cost = 0;
for (i = 0; i < spanlist.n; i++) {
printf("\n%d - %d : %d", spanlist.data[i].u, spanlist.data[i].v, spanlist.data[i].w);
cost = cost + spanlist.data[i].w;
}
printf("\nSpanning tree cost: %d", cost);
}
int main() {
int i, j, total_cost;
n = 6;
Graph[0][0] = 0;
Graph[0][1] = 4;
Graph[0][2] = 4;
Graph[0][3] = 0;
Graph[0][4] = 0;
Graph[0][5] = 0;
Graph[0][6] = 0;
Graph[1][0] = 4;
Graph[1][1] = 0;
Graph[1][2] = 2;
Graph[1][3] = 0;
Graph[1][4] = 0;
Graph[1][5] = 0;
Graph[1][6] = 0;
Graph[2][0] = 4;
Graph[2][1] = 2;
Graph[2][2] = 0;
Graph[2][3] = 3;
Graph[2][4] = 4;
Graph[2][5] = 0;
Graph[2][6] = 0;
Graph[3][0] = 0;
Graph[3][1] = 0;
Graph[3][2] = 3;
Graph[3][3] = 0;
Graph[3][4] = 3;
Graph[3][5] = 0;
Graph[3][6] = 0;
Graph[4][0] = 0;
Graph[4][1] = 0;
Graph[4][2] = 4;
Graph[4][3] = 3;
Graph[4][4] = 0;
Graph[4][5] = 0;
Graph[4][6] = 0;
Graph[5][0] = 0;
Graph[5][1] = 0;
Graph[5][2] = 2;
Graph[5][3] = 0;
Graph[5][4] = 3;
Graph[5][5] = 0;
Graph[5][6] = 0;
kruskalAlgo();
print();
}// Kruskal's algorithm in Java
import java.util.*;
class Graph {
class Edge implements Comparable<Edge> {
int src, dest, weight;
public int compareTo(Edge compareEdge) {
return this.weight - compareEdge.weight;
}
};
// Union
class subset {
int parent, rank;
};
int vertices, edges;
Edge edge[];
// Graph creation
Graph(int v, int e) {
vertices = v;
edges = e;
edge = new Edge[edges];
for (int i = 0; i < e; ++i)
edge[i] = new Edge();
}
int find(subset subsets[], int i) {
if (subsets[i].parent != i)
subsets[i].parent = find(subsets, subsets[i].parent);
return subsets[i].parent;
}
void Union(subset subsets[], int x, int y) {
int xroot = find(subsets, x);
int yroot = find(subsets, y);
if (subsets[xroot].rank < subsets[yroot].rank)
subsets[xroot].parent = yroot;
else if (subsets[xroot].rank > subsets[yroot].rank)
subsets[yroot].parent = xroot;
else {
subsets[yroot].parent = xroot;
subsets[xroot].rank++;
}
}
// Applying Krushkal Algorithm
void KruskalAlgo() {
Edge result[] = new Edge[vertices];
int e = 0;
int i = 0;
for (i = 0; i < vertices; ++i)
result[i] = new Edge();
// Sorting the edges
Arrays.sort(edge);
subset subsets[] = new subset[vertices];
for (i = 0; i < vertices; ++i)
subsets[i] = new subset();
for (int v = 0; v < vertices; ++v) {
subsets[v].parent = v;
subsets[v].rank = 0;
}
i = 0;
while (e < vertices - 1) {
Edge next_edge = new Edge();
next_edge = edge[i++];
int x = find(subsets, next_edge.src);
int y = find(subsets, next_edge.dest);
if (x != y) {
result[e++] = next_edge;
Union(subsets, x, y);
}
}
for (i = 0; i < e; ++i)
System.out.println(result[i].src + " - " + result[i].dest + ": " + result[i].weight);
}
public static void main(String[] args) {
int vertices = 6; // Number of vertices
int edges = 8; // Number of edges
Graph G = new Graph(vertices, edges);
G.edge[0].src = 0;
G.edge[0].dest = 1;
G.edge[0].weight = 4;
G.edge[1].src = 0;
G.edge[1].dest = 2;
G.edge[1].weight = 4;
G.edge[2].src = 1;
G.edge[2].dest = 2;
G.edge[2].weight = 2;
G.edge[3].src = 2;
G.edge[3].dest = 3;
G.edge[3].weight = 3;
G.edge[4].src = 2;
G.edge[4].dest = 5;
G.edge[4].weight = 2;
G.edge[5].src = 2;
G.edge[5].dest = 4;
G.edge[5].weight = 4;
G.edge[6].src = 3;
G.edge[6].dest = 4;
G.edge[6].weight = 3;
G.edge[7].src = 5;
G.edge[7].dest = 4;
G.edge[7].weight = 3;
G.KruskalAlgo();
}
}# Kruskal's algorithm in Python
class Graph:
def __init__(self, vertices):
self.V = vertices
self.graph = []
def add_edge(self, u, v, w):
self.graph.append([u, v, w])
# Search function
def find(self, parent, i):
if parent[i] == i:
return i
return self.find(parent, parent[i])
def apply_union(self, parent, rank, x, y):
xroot = self.find(parent, x)
yroot = self.find(parent, y)
if rank[xroot] < rank[yroot]:
parent[xroot] = yroot
elif rank[xroot] > rank[yroot]:
parent[yroot] = xroot
else:
parent[yroot] = xroot
rank[xroot] += 1
# Applying Kruskal algorithm
def kruskal_algo(self):
result = []
i, e = 0, 0
self.graph = sorted(self.graph, key=lambda item: item[2])
parent = []
rank = []
for node in range(self.V):
parent.append(node)
rank.append(0)
while e < self.V - 1:
u, v, w = self.graph[i]
i = i + 1
x = self.find(parent, u)
y = self.find(parent, v)
if x != y:
e = e + 1
result.append([u, v, w])
self.apply_union(parent, rank, x, y)
for u, v, weight in result:
print("%d - %d: %d" % (u, v, weight))
g = Graph(6)
g.add_edge(0, 1, 4)
g.add_edge(0, 2, 4)
g.add_edge(1, 2, 2)
g.add_edge(1, 0, 4)
g.add_edge(2, 0, 4)
g.add_edge(2, 1, 2)
g.add_edge(2, 3, 3)
g.add_edge(2, 5, 2)
g.add_edge(2, 4, 4)
g.add_edge(3, 2, 3)
g.add_edge(3, 4, 3)
g.add_edge(4, 2, 4)
g.add_edge(4, 3, 3)
g.add_edge(5, 2, 2)
g.add_edge(5, 4, 3)
g.kruskal_algo()