Kruskal’s algorithm:
Kruskal‟s algorithm finds the minimum spanning tree for a weighted connected graph G=(V,E) to get an acyclic subgraph with |V|-1 edges for which the sum of edge weights is the smallest. Consequently the algorithm constructs the minimum spanning tree as an expanding sequence of subgraphs, which are always acyclic but are not necessarily connected on the intermediate stages of algorithm. The algorithm begins by sorting the graph‟s edges in non decreasing order of their weights. Then starting with the empty subgraph, it scans the sorted list adding the next edge on the list to the current subgraph if such an inclusion does not create a cycle and simply skipping the edge otherwise.
Complexity: With an efficient sorting algorithm, the time efficiency of kruskal‟s algorithm will be in O(|E| log |E|).
#include<stdio.h>
#include<conio.h>
#include<stdlib.h>
int i,j,k,a,b,u,v,n,ne=1;
int min,mincost=0,cost[9][9],parent[9];
int find(int);
int uni(int,int);
void main()
{
clrscr();
printf("\n\n\tImplementation of Kruskal's algorithm\n\n");
printf("\nEnter the no. of vertices\n");
scanf("%d",&n);
printf("\nEnter the cost adjacency matrix\n");
for(i=1;i<=n;i++)
{
for(j=1;j<=n;j++)
{
scanf("%d",&cost[i][j]);
if(cost[i][j]==0)
cost[i][j]=999;
}
}
printf("\nThe edges of Minimum Cost Spanning Tree are\n\n");
while(ne<n)
{
for(i=1,min=999;i<=n;i++)
{
for(j=1;j<=n;j++)
{
if(cost[i][j]<min)
{
min=cost[i][j];
a=u=i;
b=v=j;
}
}
}
u=find(u);
v=find(v);
if(uni(u,v))
{
printf("\n%d edge (%d,%d) =%d\n",ne++,a,b,min);
mincost +=min;
}
cost[a][b]=cost[b][a]=999;
}
printf("\n\tMinimum cost = %d\n",mincost);
getch();
}
int find(int i)
{
while(parent[i]) i=parent[i];
return i;
}
int uni(int i,int j)
{
if(i!=j)
{
parent[j]=i;
return 1;
}
return 0;
}
