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Show that for any integer n that is a power of 2 , there is an instance of the set cover problem (Section 5.4) with the following properties:

  1. There are n elements in the base set.
  2. The optimal cover uses just two sets.
  3. The greedy algorithm picks at least log n sets.

Thus the approximation ratio we derived in the chapter is tight.

Short Answer

Expert verified

Any integer which count with 2 or count with power of 2 it gives elements in base set and optimal cover using two set in greedy algorithm.

Step by step solution

01

Elements of Even /Odd Numbers

Represent a set with n items that would be a positive integer of 2 . Permit the collection to be. (1,2,...,2k) for some K2.

So ideal number of matches would be two. • One has even numbers, while the other has odd numbers. As a result, the two sets will be localid="1658922602021" X=1,3,...,2k-3,2k-1 andY=2,4,...,2k-2,2k.Y=2,4,...,2k-2,2k..

02

Algorithm of number of 2 ’s in odd / even calculation

Now, Take, for example, a greedy algorithm.

Take into account everything. i ,

Let Di=2(k-1),2(k-i)+1,...,2k-i+1.

Clearly,

A=i=1kD1

Asn=2k

Thus,logn=k

Its foundation setting is the combination of sets handled by greedy.

• Although X and Y do not cover and over half of both the elements, they provide the best solution.

D1, on the other hand, actually covers one additional vertex than X or Y .

As a result, there is a close approximated ratio among both greedy and optimum solutions.

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Most popular questions from this chapter

The basic intuition behind Huffman’s algorithm, that frequent blocks should have short encodings and infrequent blocks should have long encodings, is also at work in English, where typical words like I, you, is, and, to, from, and so on are short, and rarely used words like velociraptor are longer.

However, words like fire!, help!, and run! are short not because they are frequent, but perhaps because time is precious in situations where they are used.

To make things theoretical, suppose we have a file composed of m different words, with frequencies f1,...,fm. Suppose also that for the ithword, the cost per bit of encoding is ci. Thus, if we find a prefix-free code where the ithword has a codeword of length Ii, then the total cost of the encoding will be localid="1659078764835" fi·ci·li.

Show how to modify Huffman’s algorithm to find the prefix-free encoding of minimum total cost.

In this problem, we will develop a new algorithm for finding minimum spanning trees. It is based upon the following property:

Pick any cycle in the graph, and let e be the heaviest edge in that cycle. Then there is a minimum spanning tree that does not contain e.

(a) Prove this property carefully.

(b) Here is the new MST algorithm. The input is some undirected graph G=(V,E) (in adjacency list format) with edge weights {we}.sort the edges according to their weights for each edge eE, in decreasing order of we:

if e is part of a cycle of G:

G = G - e (that is, remove e from G )

return G , Prove that this algorithm is correct.

(c) On each iteration, the algorithm must check whether there is a cycle containing a specific edge . Give a linear-time algorithm for this task, and justify its correctness.

(d) What is the overall time taken by this algorithm, in terms of |E|? Explain your answer.

A binary counter of unspecified length supports two operations: increment (which increases its value by one) and reset (which sets its value back to zero). Show that, starting from an initially zero counter, any sequence of n increment and reset operations takes time O(n); that is, the amortized time per operation is O(1) .

Give the state of the disjoint-sets data structure after the following sequence of operations, starting from singleton sets 1,,8. Usepath compression. In the case of ties, always make the lower numbered root point to the higher numbered ones.

union1,2,union3,4,union5,6,union7,8

,union1,4,union6,7,union4,5,find1

Design a linear-time algorithm for the following task.

Input: A connected, undirected graphG.

Question:Is there an edge you can remove fromGwhile still leavingGconnected?

Can you reduce the running time of your algorithm toO(V)?

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