You are given a convex polygon P on n vertices in the plane (specified by their x and y coordinates). A triangulation of P is a collection of n-3diagonals of such that no two diagonals intersect (except possibly at their endpoints). Notice that a triangulation splits the polygon’s interior into n-2 disjoint triangles. The cost of a triangulation is the sum of the lengths of the diagonals in it. Give an efficient algorithm for finding a triangulation of minimum cost. (Hint: Label the vertices of P by 1,....,n, starting from an arbitrary vertex and walking clockwise. For 1i<jn, let the subproblem A(i,j)denote the minimum cost triangulation of the polygon spanned by vertices i,i+1,...,j.).

Short Answer

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Convex Polygon: A convex polygon is a close figure whose each interior angle is less than 180°This means that no diagonal can be made which passes outside the boundary of polygon.

Step by step solution

01

Defining the Recursive Equation of Minimum Cost Triangulation

We will make our recursive equation in such a way that no diagonal cross eachother. For numbering, we will follow clockwise direction.

If Ai,jdenote minimum cost triangulation, where i,jare different vertices, Then i,i=0as we cannot make diagonal using same vertice.

Thus, Recursive Equation is:

localid="1657271470951" Ai,j=0minikjAi,k+Ak,j+di,k+dk,j0;ifi=j

Now it is important to define the length of diagonal(d). It is given as:

di,j=xi-xj2+yi-yj220;otherwise;ifj-i2

02

Implementing Algorithm

The algorithm would be as follows:

fori=0tonAi,j=0form=1ton-1fori=1ton-mj=i+mminikjAi,j+Ak,j+di,k+dk,j

returnA1,n

03

Analyse the Algorithm

Now, the outer for loop takes0ntime to compute each of the entry ofAi,j

The two nested loop takes 0n2time. So the effective time complexity will be0n3.

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Most popular questions from this chapter

Given two strings x=x1x2···xnand y=y1y2···ym, we wish to find the length of their longest common subsequence, that is, the largest k for which there are indices i1<i2<···<ikand j1<j2<···<jkwith xi1xi2···xik=yj1yj2···yjk. Show how to do this in time 0(mn).

Sequence alignment. When a new gene is discovered, a standard approach to understanding its function is to look through a database of known genes and find close matches. The closeness of two genes is measured by the extent to which they are aligned. To formalize this, think of a gene as being a long string over an alphabet ={A,C,G,T}. Consider two genes (strings) x=ATGCCand y=TACGCA. An alignment of x and y is a way of matching up these two strings by writing them in columns, for instance:

A-T-GCCTA-CGC

Here the “_” indicates a “gap.” The characters of each string must appear in order, and each column must contain a character from at least one of the strings. The score of an alignment is specified by a scoring matrixδof size (+1)×(+1), where the extra row and column are to accommodate gaps. For instance the preceding alignment has the following score:

δ(-T)+δ(A,A)+δ(T,-)+δ(G,G)+δ(C,C)+δ(C,A)

Give a dynamic programming algorithm that takes as input two strings X[1K n] and Y {1K m} and a scoring matrix δand returns the highest-scoring alignment. The running time should be O(mn) .

Reconstructing evolutionary trees by maximum parsimony. Suppose we manage to sequence a particular gene across a whole bunch of different species. For concreteness, say there are n species, and the sequences are strings of length k over alphabet={A,C,G,T}. How can we use this information to reconstruct the evolutionary history of these species?

Evolutionary history is commonly represented by a tree whose leaves are the different species, whose root is their common ancestor, and whose internal branches represent speciation events (that is, moments when a new species broke off from an existing one). Thus we need to find the following:

• An evolutionary tree with the given species at the leaves.

• For each internal node, a string of length K: the gene sequence for that particular ancestor.

For each possible tree T annotated with sequencess(u)kat each of its nodes , we can assign a score based on the principle of parsimony: fewer mutations are more likely.

localid="1659249441524" score(T)=(u.v)E(T)(numberofpositionsonwhichs(u)ands(v)disagree)

Finding the highest-score tree is a difficult problem. Here we will consider just a small part of it: suppose we know the structure of the tree, and we want to fill in the sequences s(u) of the internal nodes u. Here’s an example with k=4 and n=5:


(a) In this particular example, there are several maximum parsimony reconstructions of the internal node sequences. Find one of them.

(b) Give an efficient (in terms of n and k ) algorithm for this task. (Hint: Even though the sequences might be long, you can do just one position at a time.)

You are given a string of n characters s[1...n], which you believe to be a corrupted text document in which all punctuation has vanished (so that it looks something like “itwasthebestoftimes...”). You wish to reconstruct the document using a dictionary, which is available in the form of a Boolean function dict(.): for any string w,

dict(w)={trueifwisavalidwordfalseotherwise

Give a dynamic programming algorithm that determines whether the string s[.]can be reconstituted as a sequence of valid words. The running time should be at mostO(n2) , assuming calls to dict take unit time.

In the event that the string is valid, make your algorithm output the corresponding sequence of words.

Consider the following 3-PARTITION problem. Given integersa1,...,an, we want to determine whether it is possible to partition of {1,...,n} into three disjoint subsets I,J,Ksuch that

aiiI=ajjJ=akkk=13aii1 .

For example, for input(1,2,3,4,4,5,8) the answer is yes, because there is the partition(1,8),(4,5),(2,3,4). On the other hand, for input(2,2,3,5) the answer is no. Devise and analyze a dynamic programming algorithm3-PARTITION for that runs in time polynomial in n and in Σiai.

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