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A) Write the pseudocode for an algorithm using dynamic programming to solve the activity-selection problem based...
1. Write the algorithm pseudocode for the longest common subsequence problem using dynamic programming. What is its running time?
Give a dynamic programming algorithm that runs within the time complexity. Also give the space complexity of the algorithm. Please Given a directed graph with non-negative integer edge weights, a pair of vertices s and t, and integers K and W, describe a dynamic-programming algorithm for deciding whether there exists a path from s to t that has total weight W and uses exactly K edges. Your algorithm should run in time O(nm)WK). Analyze the time- and space-complexity of your...
The Egg Drop problem asks us to find the fewest number of egg dropping trials we need to perform in the worst case in order to identify the highest floor from which we can safely drop an egg out of an n-floor building when given k eggs. Notably, if E(n, k) represents the solution to the Egg Drop problem with n floors and k eggs, E(n, k) satisfies the following recurrence: E(n, k) = min i=1,...,n max(E(n ? i, k),...
a. Use pseudocode to specify a brute-force algorithm that takes as input a list of n positive integers and determines whether there are two distinct elements of the list that have as their sum a third element of the list. That is, whether there exists i, j.k such that iヂj, i关k,j关k and ai + aj = ak. The algorithm should loop through all triples of elements of the list checking whether the sum of the first two is the third...
Rod-cutting problem Design a dynamic programming algorithm for the following problem. Find the maximum total sale price that can be obtained by cutting a rod of n units long into integer-length pieces if the sale price of a piece i units long is pi for i = 1, 2, . . . , n. What are the time and space efficiencies of your algorithm? Code or pseudocode is not needed. Just need theoretical explanation with dynamic programming with recurrence relation...
Using sorting as an algorithm solving specific problem and compare their method of solving it and performances’ tradeoffs in terms of its time complexity. compare its performance using different approaches (three approaches) such as (divide and conquer, dynamic programming, brute force, greedy approach ). show which approach solve the problem best. Use sorting as an example and compare .
Consider the following pseudocode: Algorithm RecursiveFunction (a, b) // a and b are integers if (as1 ) return b; else return RecursiveFunction (a-2, a/2); endif a. What is the time complexity of the RecursiveFunction pseudocode shown above? b What is the space complexity of the RecursiveFunction pseudocode shown above? n(n+1) C. What is the time complexity of the following algorithm (Note that 21-, i = n(n+1)(2n+1). and Σ.,1 ): Provide both T(n) and order, Ofn)). int A=0; for (int i=0;i<n;i++)...
In terms of the programming language required, the algorithm needs to be written in pseudocode Dynamic Programming Consider the following problem based on the transformation of a sequence (or collection) of coloured disks Assume that you have a very large collection of disks, each with an integer value representing the disk colour from the range [0, c. For example, the colour mapping might be 0-red. 1-yellow, 2-blue, 3-pink. , c-black For a given sequence of coloured disks e.g., ( 0,1,2,3,4...
Modify Algorithm 3.2 (Binomial Coefficient Using Dynamic Programming) so that it uses only a one-dimensional array indexed from 0 to k. Algorithm 3.2 Binomial Coefficient Using Dynamic Programming Problem: Compute the binomial coefficient. Inputs: nonnegative integers n and k, where ks n. Outputs: bin2, the binomial coefficient (2) int bin2 (int n, int k) index i, j; int B[0..n][0..k]; for (i = 0; i <= n; i++) for (i = 0; j <= minimum( i,); ++) if (j == 0...
Give pseudocode that performs the traceback to construct an LCS from a filled dynamic programming table without using the “arrows”, in O(n + m) time. 2. Suppose we are given a “chain” of n nodes as shown below. Each node i is “neighbors” with the node to its left and the node to its right (if they exist). An independent set of these nodes is a subset of the nodes such that no two of the chosen nodes are neighbors....