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Given an undirected graphG=(V,E) in which each node hasdegreed , show how to efficiently find an independent set whose size is at least1d+1times that of the largest independent set.

Short Answer

Expert verified

This algorithm is proved.

Step by step solution

01

Step 1:

An undirected graph in which each node has degree ≤ d, efficiently an independent set whose size is at least1d+1 times that of the largest independent set is defined below.

02

Step 2:  

LetG be the graph with vertex set of V having d the maximum degree, and in an empty set.

The following process will get an independent set whose size is atleast1d+1 times that of the largest independent set.

1). Pick a vertex with smallest degree and add to it.

2). Delete vertex and all its adjacent vertices from the graph.

3). Repeat this process until the vertex set is empty.

The set is now the independent set of the graphG .

Since a vertex in the graph has most d neighbours , thus at each iteration , maximum d+1vertices are deleted. Thus, the vertex set reduces byd+1 vertices at each and every iteration.

Hence there are atleast|V|(d+1) iteration to get the I. At each iteration, one vertex is added in the set I.

Hence, I contains atleat |V|(d+1)vertices.

|V|(d+1)

Let k be the size of the maximum independent as |V|K

Therefore,

|1|    |V|(d+1)Kd+1

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Most popular questions from this chapter

In the MULTIWAY CUT problem, the input is an undirected graphG=(V,E) and a set of terminal nodess1,s2,...,skV. The goal is to find the minimum set of edges in whose removal leaves all terminals in different components.

(a) Show that this problem can be solved exactly in polynomial time when k=2.

(b) Give an approximation algorithm with ratio at most2 for the case k=3.

(c) Design a local search algorithm for multiway cut.

In the backtracking algorithm for SAT, suppose that we always choose a subproblem (CNF formula) that has a clause that is as small as possible; and we expand it along a variable that appears in this small clause. Show that this is a polynomial-time algorithm in the special case in which the input formula has only clauses with two literals (that is, it is an instance of 2SAT).

Devise a backtracking algorithm for the RUDRATA PATH problem from a fixed vertex s. To fully specify such an algorithm you must define:

(a) What is a subproblem?

(b) How to choose a subproblem.

(c) How to expand a subproblem.

Argue briefly why your choices are reasonable

In the MINIMUM STEINER TREE problem, the input consists of: a complete graph G=(V,E)with distances duvbetween all pairs of nodes; and a distinguished set of terminal nodesV'V.The goal is to find a minimum-cost tree that includes the vertices V'. This tree may or may not include nodes in V-V'

Suppose the distances in the input are a metric (recall the definition on page 292). Show that an efficient ratio-2approximation algorithm for MINIMUM STEINER TREE can be obtained by ignoring the nonterminal nodes and simply returning the minimum spanning tree onV'. (Hint: Recall our approximation algorithm for the TSP.)

Local search for minimum spanning trees. Consider the set of all spanning trees (not just minimum ones) of a weighted, connected, undirected graphG=(V,E).

Recall from Section 5.1 that adding an edge to a spanning treeT creates an unique cycle, and subsequently removing any other edgee'e from this cycle gives back a different spanning treeT' . We will say that differ by a single edge swap (e,e')and that they are neighbors.

a) Show that it is possible to move from any spanning tree Tto any other spanning tree T' by performing a series of edge-swaps, that is, by moving from neighbor to neighbor. At most how many edge-swaps are needed?

(b) Show that ifT' is an MST, then it is possible to choose these swaps so that the costs of the spanning trees encountered along the way are nonincreasing. In other words, if the sequence of spanning trees encountered is

T=T0T1T2···Tk=T',

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(c) Consider the following local search algorithm which is given as input an undirected graph G.

Let Tbe any spanning tree of G

while there is an edge-swap(e,e') which reduces cost(T):

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Show that this procedure always returns a minimum spanning tree. At most how many iterations does it take ?

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