There are n items in a store. For each item i=1,2,...,n the weight of the item is wi and the value of the item is vi. A thief is carrying a knapsack of weight W. In this version of a problem the items can be broken into smaller pieces, so the thief may decide to carry only a fraction xi of object i, where 0≤xi ≤1. Item i contributes xiwi to the total weight in the knapsack, and xivi to the value of the load. Find the maximum value that the thief can fill in his knapsack. Part A: (20%)Write pseudocode for the algorithm to solve this problem. Part B: (5%)What is the complexity of this algorithm? Part C: (5%)What is the archetype of this algorithm?
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There are n items in a store. For each item i=1,2,...,n the weight of the item...
Recall that in the "Knapsack Problem", there are n items having respective values V1..n) and weights W1..n), all greater than 0 and one needs to maximize the total value of the subset of the items placed in the knapsack limited by a weight capacity of W In the 0-1 Knapsack Problem, each item must be either be included or excluded in its entirety, in light of the fact that this problem is to be "NP-Complete", how can one solve the...
1. Fractional Knapsack Problem Algorithm Which best describes the tightest range of the number of items with only fractional inclusion (i.e. not entirely included or excluded) in the knapsack? (Let n denote the number of items for possible inclusion.) A) At least 0 items and at most n items B) At least 1 items and at most n items C) Exactly n items D) At least 0 items and at most n-1 items E) At least 1 items and at...
2 Knapsack Problem In a Knapsack problem, given n items {11, I2, -.., In} with weight {wi, w2, -.., wn) and value fvi, v2, ..., vn], the goal is to select a combination of items such that the total value V is maximized and the total weight is less or equal to a given capacity W. Tt i=1 In this question, we will consider two different ways to represent a solution to the Knapsack problem using an array with size...
"Greedy, but Better": Given a knapsack problem with a weight capacity C, and n items, and each item has a weight W[1:n] and monetary value P[1:n]. You have to determine which items to take so that the total weight is C, and the total value (profit) is maximized. In this case we are considering an integer problem, so you can either take an item, or not take an item, you cannot take it fractionally. If you recall, the greedy algorithm...
Design a local search algorithm for the 0-1 knapsack problem. Assume there are n items x1 ... xn each with weight wi and value vi. The knapsack can have at most one of each item and the total weight cannot exceed W. You want to maximize the total value in the knapsack.Question 1: (7 points) Show the psuedocode/explanation for your algorithm.Question 2. (3 points) Is it guaranteed to find an optimal solution? Justify your answer.
In a Knapsack problem, given n items {I1, I2, · · · , In} with weight {w1, w2, · · · , wn} and value {v1,v2, ···, vn}, the goal is to select a combination of items such that the total value V is maximized and the total weight is less or equal to a given capacity W . i-1 In this question, we will consider two different ways to represent a solution to the Knapsack problem using . an...
The decision version of the Knapsack problem is as follows: Given a set of n items {1, 2, …, n}, where each item j has a value v(j) and a weight w(j), and two numbers V and W, can we find a subset X of {1, 2, …, n} such that Σj∈X v(j) ≥ V and Σj∈X w(j) ≤ W? Prove formally that the Knapsack problem is NP-complete.
solution is required in pseudo code please. 2 Knapsack Problem În al Knapsack problem. given n items(11-12. . . . . 1"} with weight {w1·W2. . . . . ux) and value (n 2, .., nJ, the goal is to select a combination of items such that the total value V is maximized and the total weight is less or equal to a given capacity In this question, we will consider two different ways to represent a solution to the...
For given capacity of knapsack W and n items {i1,i2,...,in} with its own value {v1,v2,...,vn} and weight {w1,w2,...,wn}, find a greedy algorithm that solves fractional knapsack problem, and prove its correctness. And, if you naively use the greedy algorithm to solve 0-1 knapsack problem with no repetition, then the greedy algorithm does not ensure an optimal solution anymore. Give an example that a solution from the greedy algorithm is not an optimal solution for 0-1 knapsack problem.
I'm having trouble with my Java Homework in which my professor wants us to solve the 0-1 Knapsack problem with Dynamic Programming. The code below is what she provided and she requested that we not change any of her existing code but simply add to it. As you can see she gave us the stub file for the knapsack class and the Item class. You are a thief with a knapsack with a carrying capacity of knapsackCapacity pounds. You want...