Apply the bottom-up dynamic programming algorithm to the following instance of the knapsack problem: Item Weight Value 1 3 $25 2 2 $30 3 1 $15 4 4 $40 5 5 $50 Capacity W = 8.
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Apply the bottom-up dynamic
instance of the knapsack problem:
| Item | Weight | Value |
| 1 | 3 | $25 |
| 2 | 2 | $30 |
| 3 | 1 | $15 |
| 4 | 4 | $40 |
| 5 | 5 | $50 |
Capacity W = 8.
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- Consider the use of a genetic algorithm on this 0-1 Knapsack Problem W = 19 P1 = 20, w1 = 2 P2 = 30, w2 = 6 P3 = 36, w2 = 9 P4 = 16, w3 = 8 If an individual in the population is given the string: "0,1,0,1" then the measure of fitness would be?Which type of best first search algorithm was used to predict the closeness of the end of path and its solution? a) Greedy BFS b) Divide and Conquer c) Heuristic BFS d) Combinatorialillustrate Algorithm to the procedure to obtain the optimal binary search tree,given the list of keys ? = {a 1, a 2, ? 3,…? n} and the probabilities ? i,1≤ ? ≤? and? i,0≤ ? ≤?.
- Q: Apply the dynamic algorithm of Knapsack problem for the following inputs. Knapsack of capacity W = 10 item weight value 1 1 $10 2 2 $40 3 1 $20 4 3 $20 5 5 $60Is it true that a greedy algorithm always finds the best solution? Justify your response.If an optimal solution to a problem can be obtained by greedy, It can also be obtained by dynamic programming. True or False?
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