Kruskals algorithm, Data Structure & Algorithms

Assignment Help:

Krushkal's algorithm uses the concept of forest of trees. At first the forest contains n single node trees (and no edges). At each of the step, we add on one (the cheapest one) edge so that it links two trees together. If it makes a cycle, simply it would mean that it links two nodes that were connected already. So, we reject it.

The steps in Kruskal's Algorithm are as:

1.   The forest is constructed through the graph G - along each node as a separate tree in the forest.

2.   The edges are placed within a priority queue.

3.   Do till we have added n-1 edges to the graph,

  I.   Extract the lowest cost edge from the queue.

 II.   If it makes a cycle, then a link already exists among the concerned nodes. So reject it.

 III.  Otherwise add it to the forest. Adding it to the forest will join two trees together.

The forest of trees is a division of the original set of nodes. At first all the trees have exactly one node in them. As the algorithm progresses, we make a union of two of the trees (sub-sets), until the partition has only one sub-set containing all the nodes eventually.

Let us see the sequence of operations to determine the Minimum Cost Spanning Tree(MST) in a graph via Kruskal's algorithm. Suppose the graph of graph shown in figure  and below figure  illustrates the construction of MST of graph of Figure

1339_Kruskals Algorithm.png

Figure: A Graph

Figure: Construction of Minimum Cost Spanning Tree for the Graph by application of Kruskal's algorithm

The following are several steps in the construction of MST for the graph of Figure via Kruskal's algorithm.

Step 1 :  The lowest cost edge is chosen from the graph that is not in MST (initially MST is empty). The cheapest edge is 3 that is added to the MST (illustrated in bold edges)

Step 2: The next cheap edge which is not in MST is added (edge with cost 4).

Step 3 : The next lowest cost edge that is not in MST is added (edge with cost 6).

 Step 4 : The next lowest cost edge that is not in MST is added (edge with cost 7).

Step 5 : The next lowest cost edge that is not in MST is 8 but form a cycle. Hence, it is discarded. The next lowest cost edge 9 is added. Now the MST has all the vertices of the graph. This results in the MST of the original graph.


Related Discussions:- Kruskals algorithm

Explain all-pair shortest-paths problem, Explain All-pair shortest-paths pr...

Explain All-pair shortest-paths problem Given a weighted linked graph (undirected or directed), the all pairs shortest paths problem asks to find the distances (the lengths of

Addressing modes, Compare zero-address, one-address, two-address, and three...

Compare zero-address, one-address, two-address, and three-address machines by writing programs to compute: Y = (A – B X C) / (D + E X F) for each of the four machines. The inst

A sort which relatively passes by a list, A Sort which relatively passes by...

A Sort which relatively passes by a list to exchange the first element with any element less than it and then repeats with a new first element is called as      Quick sort.

Sparse matrix, memory address of any element of lower left triangular spars...

memory address of any element of lower left triangular sparse matrix

All pairs shortest paths algorithm, In the last section, we discussed regar...

In the last section, we discussed regarding shortest path algorithm that starts with a single source and determines shortest path to all vertices in the graph. In this section, we

How to construct binary tree, Q. A Binary tree comprises 9 nodes. The preor...

Q. A Binary tree comprises 9 nodes. The preorder and inorder traversals of the tree yield the given sequence of nodes: Inorder :          E     A    C    K    F     H    D

Explain dijkstra''s algorithm, Explain Dijkstra's algorithm Dijkstra's ...

Explain Dijkstra's algorithm Dijkstra's algorithm: This problem is concerned with finding the least cost path from an originating node in a weighted graph to a destination node

Binary search tree, write an algorithm to delete an element x from binary...

write an algorithm to delete an element x from binary search with time complex

Sparse matrix, How sparse matrix stored in the memory of a computer?

How sparse matrix stored in the memory of a computer?

Explain optimal binary search trees, Explain Optimal Binary Search Trees ...

Explain Optimal Binary Search Trees One of the principal application of Binary Search Tree is to execute the operation of searching. If probabilities of searching for elements

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd