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.

Short Answer

Expert verified

The given strategy fails when the shortest cycle consists of more than the one back edge.

Step by step solution

01

Define graphs

A graph consists of nodes and edges. These nodes are also known as vertices. In undirected graphs, the nodes are connected by bidirectional edges. On the other hand, a directed graph is one in which all of the edges point in some particular direction.

02

Determine a counter example where the given strategy fails

The node's level is equal to its distance of the node from the root node. If there are more than one back edges in the shortest cycle, the given strategy to find the shortest cycle in an undirected graph fails. Consider the following graph:

The above diagram illustrates an undirected graph. In this undirected graph, the shortest cycle would be 1451. But the given algorithm would detect 12341.

Hence, it can be concluded that the given strategy fails when the shortest cycle consists of more than one back edge.

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Most popular questions from this chapter

In cases where there are several different shortest paths between two nodes (and edges have varying length),the most convenient of these paths is often the one with fewest edges. Forinstance, if nodes represent cities and edge lengths represent costs of flying between cities, theremight be many ways to get from cityto city t which all have the same cost. The mostconvenientof these alternatives is the one which involves the fewest stopovers. Accordingly, for a specific starting node S , define

bestu=minimum number of edges in a shortest path from S to u .

In the example below, thebestvalues for nodes S,A,B,C,D,E,Fare 0,1,1,1,2,2,3, respectively.

Give an efficient algorithm for the following problem.

Input:Graph G=V,E; positive edge lengths le; starting node sV.

Output: The values of bestu should be set for all nodesuV

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.

Question: Often there are multiple shortest paths between two nodes of a graph. Give a linear-time algorithm for the following task.

Input: Undirected graph G = (V , E )with unit edge lengths; nodesu,vV

Output: The number of distinct shortest paths from utov.

Shortest path algorithms can be applied in currency trading. Let c1,c2,cn be various currencies; for instance, c1might be dollars, c2pounds, and c3 lire.

For any two currencies ci and cj , there is an exchange rate τi,j; this means that you can purchase τi,j units of currency cj in exchange for one unit of cj. These exchange rates satisfy the condition that rij.rji<1 so that if you start with a unit of currency cj, change it into currency and then convert back to currency localid="1658917254028" ci, you end up with less than one unit of currency ci (the difference is the cost of the transaction).

a. Give an efficient algorithm for the following problem: Given a set of exchange rates rij , and two currencies s and t , find the most advantageous sequence of currency exchanges for converting currency into currency . Toward this goal, you should represent the currencies and rates by a graph whose edge lengths are real numbers.

The exchange rates are updated frequently, rejecting the demand and supply of the various currencies. Occasionally the exchange rates satisfy the following property: there is a sequence of currencies ci1,ci2,.......ciksuch that ri1,ri2.i3,.........ri(k-1),ik,rik+1>1. This means that by starting with a unit of currency ci1and then successively converting it to currencies ci1,ci2.......cik, and finally back to ci1, you would end up with more than one unit of currency ci1 . Such anomalies Last only a fraction of a minute on the currency exchange, but they provide an opportunity for risk-free profits.

b. Give an efficientalgorithm for detecting the presence of such an anomaly. Use the graph representation you found above.

Give an O|V|2algorithm for the following task.

Input:An undirected graph G=(V,E); edge lengths Ie>0;an edge eE.

Output:The length of the shortest cycle containing edge e

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