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Squares.Design and analyse an algorithm that takes as input an undirected graph G(V,E) and determines whether graph contains a simple cycle (that is, a cycle which doesn’t intersect itself) of length four. Its running time should be at mostO(V3) time.

You may assume that the input graph is represented either as an adjacency matrix or with adjacency lists, whichever makes your algorithm simpler.

Short Answer

Expert verified

The algorithm covers a shortest distance from the vertex A to vertexD is13 and the graph will takeO|v3| running time.

Step by step solution

01

Define the concept of the algorithm used for undirected graph

Dijkstra algorithm is an application of single source shortest path.

Dijkstra’s algorithm also known as SPF algorithm and is an algorithm for finding the shortest paths between the vertices in a graph. It returns a search tree for all the paths the given node can take. An acyclic graph is a directed graph that has no cycles. Its operation is performed in the minheap.

02

Time complexity of Dijkstra algorithm.

Time complexity:

TC=V+VlogV+E+ElogVTC=VlogV+ElogVTC=OV+ElogV

When the given graph is complete graph then,

role="math" localid="1659328321979" E=V2O(V2+V2.V)O(V2+V3)O(V3)TC=OV3

For finding the shortest path adjacent list and minheap both may use.

The time complexity is

And, if the graph is acyclic than also the complexity is:OV3

03

Design the Algorithm.

Dijkstra algorithm apply on the graph for finding the single source shortest path.

A directed graph with positive edge lengths, and returns the length of the shortest cycle in the graph and the graph is acyclic, which take time at mostOV3

So, here the vertex A is the source vertex. now take a minheap as a data structure for evaluate single source shortest path between the source and the destination.

From A the distance of A is zero and take the distance of vertex A from each and every vertex is infinity.

Theinput graph is represented either as an adjacency matrix or with adjacency lists is used to stored the vertices of the graph.

Now take A as the first vertex and evaluate the weight towards each vertex.

And choose the next vertex from the vertices which have minimum weight and select that node as the second vertex.

Then again evaluate the distance of it from every vertex and as get the minimum weight of the node and consider it as the main node.

Through this the series of vertex are arises.

here the vertex A is the source vertex. now take a minheap as a data structure for evaluate single source shortest path between the source and the destination.

From A the distance of A is zero and take the distance of vertex A from each and every vertices is infinity.

Select every vertex one by one and put it into the min heap as a data structure one by one as shown in the figure.

Fig: Adjacency list of the given graph

Hence, the shortest distance from the vertex A to vertex D is 13 .

And the graph will take OV3time.

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Most popular questions from this chapter

You are given a strongly connected directed graph G=(V,E) with positive edge weights along with a particularv0∈V . Give an efficient algorithm for finding shortest paths between all pairs of nodes, with the one restriction that these paths must all pass throughv0 .

Here's a proposal for how to find the length of the shortest cycle in an undirected graph with unit edge lengths. When a back edge, say (v,w), is encountered during a depth-first search, it forms a cycle with the tree edges from wtov. The length of the cyclelevel[v]-level[w+1] is where the level of a vertex is its distance in the DFS tree from the root vertex. This suggests the following algorithm:

• Do a depth-first search, keeping track of the level of each vertex.

• Each time a back edge is encountered, compute the cycle length and save it if it is smaller than the shortest one previously seen. Show that this strategy does not always work by providing a counterexample as well as a brief (one or two sentence) explanation.

You are given a set of cities, along with the pattern of highways between them, in the form of an undirected graph G = (V , E). Each stretch of highway e∈Econnects two cities, and you know its length in miles, le. You want to get from city s to city t. There’s one problem: your car can only hold enough gas to cover L miles. There are gas stations in each city, but not between cities. Therefore, you can only take a route if every one of its edges has length le≤L

(a) Given the limitation on your car’s fuel tank capacity, show how to determine in linear time whether there is a feasible route from sto t.

(b) You are now planning to buy a new car, and you want to know the minimum fuel tank capacity that is needed to travel from s to t. Give anO[(V+E)log|V|]algorithm to determine this.

Question: Prove that for the array prev computed by Dijkstra's algorithm, the edges {u,prepu}(forall∈v)form a tree.

Professor F. Lake suggests the following algorithm for finding the shortest path from node to node t in a directed graph with some negative edges: add a large constant to each edge weight so that all the weights become positive, then run Dijkstra’s algorithm starting at node s , and return the shortest path found to node t .

Is this a valid method? Either prove that it works correctly, or give a counterexample.

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