Assignment 5
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- I have spent hours on internet to find an example of iterative lengthening search algorithm but found nothing. I need it ASAP. Can anyone help me? Please. It is its definition: Iterative lengthening search is an iterative analogue of uniform-cost search. The basic idea is to use increasing limits on path cost. If a node is generated whose path cost exceeds the current limit, it is immediately discarded. For each new iteration, the limit is set to the lowest path cost of any node discarded in the previous iteration. I dont understand many things in this definition. 1-What is the first limit before we start? 2-Do we delete the discarded node from the graph or what? 3-What is the generated node? Is it expanded or is it just found as neigbor? 4-What is "lowest path cost of any node discarded"?? Path from where to where?? From start to that node or what? 5-What does path cost mean in this problem? Is it from source to the new node or between current node and next chosen node? I am literally…Write Algorithm for Straightforward pairings for a round robin tournament.in: round index r (0 ≤ r ≤ 2 · (n − 1)/2); number of players n (1 ≤ n)out: sequence R of n player indices indicating the match pairings between players R2i and R2i+1, when i = 0,..., n/2 − 1; if n is odd, Rn−1 indicates the restingplayerWrite a recurrence that would be used in dynamic programming for thefollowing problem: Given a rod of length n and an array A of prices thatcontain all prices of all the pieces smaller than n. Determine the maximumvalue obtained by cutting up the rod and selling the pieces. Note that youcould sell the rod at its original length without cutting it.
- Procedure 1 (Local Search(y) with depth δ) t := 1.While t ≤ δ and ∃z : (H(z,y)=1 and f(z) > f(y)) do y := z. t := t + 1.If there is more than one Hamming neighbor with larger fitness, z may be chosen arbitrarily among them.Algorithm 1 ((1+1) Memetic Algorithm ((1+1) MA))Procedure 1 (Local Search(y) with depth δ) t := 1.While t ≤ δ and ∃z : (H(z,y)=1 and f(z) > f(y)) do y := z. t := t + 1.If there is more than one Hamming neighbor with larger fitness, z may be chosen arbitrarily among them.Algorithm 1 ((1+1) Memetic Algorithm ((1+1) MA)) write correct algorithm otherwise you will get downvote.Use & for •, v for V, > for Ɔ, and = for = What can you derive by applying De Morgan's (DM) to this formula: ~(N • E) Ɔ G (N v E) > G O (-N v -E) > G O (N & E) v G O (N & E) v G O (N v E) > G O (N & E) > G
- Algorithm to An iterative solution to Towers of Hanoi.in: triplet S = s0, s1, s2 representing the current game stateout: triplet R = r0, r1, r2 representing the new game statelocal: pole indices a, b, z ∈ {0, 1, 2}; disc numbers g, h ∈ [2, n]; last(Q) = Q|Q|−1, if1 ≤ |Q|, otherwise, last(Q) = +∞GIVEN: n red points and n blue points in the plane in general position (i.e., no 3 points are on the same line) PROVE: there exists a matching (i.e., 1-1 correspondence) between red and blue points such that the segments connecting the corresponding points do not intersect. EXTRA/HINT: describe an algorithm for finding such matchingImplement the algorithm for an optimal parenthesization of a matrix chain product as dis-cussed in the class.Use the following recursive function as part of your program to print the outcome, assumethe matrixes are namedA1, A2, ..., An.PRINT-OPTIMAL-PARENS(s, i, j){if (i=j) thenprint “A”i else{print “(”PRINT-OPTIMAL-PARENS(s,i,s[i, j])PRINT-OPTIMAL-PARENS(s, s[i, j] + 1, j)print “)”} }a- Test your algorithm for the following cases:1. Find and print an optimal parenthesization of a matrix-chain product whose sequenceof dimensions is<5,10,3, X,12,5,50, Y,6>.2. Find and print an optimal parenthesization of a matrix-chain product whose sequenceof dimensions is<5,10,50,6, X,15,40,18, Y,30,15, Z,3,12,5>. 3. Find and print an optimal parenthesization of a matrix-chain product whose sequenceof dimensions is<50,6, X,15,40,18, Y,5,10,3,12,5, Z,40,10,30,5>. X=10 Y=20 Z=30
- • Simplify the Boolean functions by means of the tabulation matching method: a. F(w,x,y,z) = Σm(2,3,12,13,14,15) b. P(m,n,o,p,q,r) =Em(6,9,13,18,19,25,27,29,41,45,57,61) c. P(A,B,C,D,E,F,G) =Σm(20,28,38,39,52,60,102,103)Prove or disprove that for any x ∈ N, x(x+1)/2 ∈ N (where N = {0, 1, 2, 3, ….}EXM.1.AHL.TZ0.37 IB [Maximum mark: 8] In this part, marks will only be awarded if you show the correct application of the required algorithms, and show all your working. In an offshore drilling site for a large oil company, the distances between the planned wells are given below in metres. 1 2 3 4 5 6 7 8 9 10 2 30 3 40 60 4 90 190 130 5 80 200 10 160 6 70 40 20 40 40 130 7 60 120 50 90 30 60 8 50 140 90 70 70 140 70 40 9 40 170 140 60 50 90 50 70 10 200 200 80 150 110 90 30 190 90 100 11 150 30 200 120 190 120 60 190 150 200 + It is intended to construct a network of paths to connect the different wells in a way that minimises the sum of the distances between them. Use Prim's algorithm, starting at vertex 3, to find a network of paths of minimum total length that can span the whole site. [8]