In weighted knapsack problem, given the knapsack capacity is 16 and the following items (Weight, Value), what is the maximum value we can take away. Explain shortly how and by what approach you arrived at this solution. Item 1 (4, 12) Item 2 (3, 14) Item 3 (7, 22) Item 4 (8, 32) Item 5 (4, 24) Item 6 (6, 20)
Go by greedy for max profit==> first go for item 4, i.e. weight 8 remaining 8, then max profit for item 5 of profit 24 and remaining weight is 4, as greedy we have to go for item 2 ==> total profit is 32+24+14=70
by greedy if go by max weight then, item4+item3=15=>32+22=54
In weighted knapsack problem, given the knapsack capacity is 16 and the following items (Weight, Value),...
"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...
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...
Solve the 0-1 knapsack problem given the following items, each labeled with weight and value. Assume the total weight limit W is 8 lbs. Item 1 Value ($) 8 Weight (lb) 1 23 4 40 30 54 2 6 3
Consider the following greedy algorithm for the knapsack problem: each time we pick the item with the highest value to weight ratio to the bag. Skip items that will make the total weight exceeded the capacity of the bag. Find a counterexample to show that this approach will not work, and the result could be 100 times worse than the optimal solution. That is, construct a table of set of items with weight and values and find a bag capacity...
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...
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...
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.
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...
1. Apply the dynamic programming algorithm discussed in class to solve the knapsack problem. (10 points) a. Show the completed table. b. Which items are included in the final configuration of the knapsack? c. What is the maximum value that can fit in the knapsack using a configuration of these items? item 1 2. 3 4 weight 3 2 value $25 $20 $15 1 capacity W = 6. 4 5 $40 $50 5
5) (10 pts) Greedy Algorithms The 0-1 Knapsack problem is as follows: you are given a list of items, each item has an integer weight and integer value. The goal of the problem is to choose a subset of the items which have a sum of weights less than or equal to a given W with a maximal sum of values. For example, if we had the following five items (each in the form (weight, value)): 11(6, 13), 2(4, 10),...