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Kruskals-Graph-Algorithm-Python

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.

#How Kruskal's Algorithm works

It falls under a class of algorithms called greedy algorithms that find the local optimum in the hopes of finding a global optimum.

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.

#Example of Kruskal's algorithm

image Start with a weighted graph

image Choose the edge with the least weight, if there are more than 1, choose anyone

image Choose the next shortest edge and add it

image Choose the next shortest edge that doesn't create a cycle and add it

image Choose the next shortest edge that doesn't create a cycle and add it

image Repeat until you have a spanning tree

#Kruskal Algorithm Pseudocode

Any minimum spanning tree algorithm revolves around checking if adding an edge creates a loop or not.

The most common way to find this out is an algorithm called Union FInd. The Union-Find algorithm divides the vertices into clusters and allows us to check if two vertices belong to the same cluster or not and hence decide whether adding an edge creates a cycle.

#Algorithm

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