Table of Contents
- 1 Is the knapsack problem difficult?
- 2 Can knapsack problem be solved in any other technique?
- 3 What is knapsack problem how can it be solved using greedy approach?
- 4 What is the use of knapsack problem?
- 5 Is there a polynomial time algorithm for knapsack optimization?
- 6 How much can I pack in my knapsack?
Is the knapsack problem difficult?
The knapsack problem is believed to be one of the “easier” -hard problems. Not only can it be solved in pseudo-polynomial time, but also decades of algorithmic improvements have made it possible to solve nearly all standard instances from the literature.
Which technique Cannot be used to solve knapsack problem?
The 0-1 Knapsack problem can be solved using Greedy algorithm. Explanation: The Knapsack problem cannot be solved using the greedy algorithm.
Can knapsack problem be solved in any other technique?
So this Knapsack problem can be solved by using these following methods: Greedy method. Dynamic Programming method. Back Tracking method.
Where are the hard knapsack problems?
Where are the hard knapsack problems? The knapsack problem is believed to be one of the “easier” NP-hard problems. Not only can it be solved in pseudo-polynomial time, but also decades of algorithmic improvements have made it possible to solve nearly all standard instances from the literature.
What is knapsack problem how can it be solved using greedy approach?
The basic idea of the greedy approach is to calculate the ratio value/weight for each item and sort the item on basis of this ratio. Then take the item with the highest ratio and add them until we can’t add the next item as a whole and at the end add the next item as much as we can.
What is NP hard problem in algorithm?
A problem is NP-hard if an algorithm for solving it can be translated into one for solving any NP- problem (nondeterministic polynomial time) problem. NP-hard therefore means “at least as hard as any NP-problem,” although it might, in fact, be harder.
What is the use of knapsack problem?
The knapsack problem is an optimization problem used to illustrate both problem and solution. It derives its name from a scenario where one is constrained in the number of items that can be placed inside a fixed-size knapsack.
What is the knapsack problem explain with suitable example?
The 0/1 knapsack problem means that the items are either completely or no items are filled in a knapsack. For example, we have two items having weights 2kg and 3kg, respectively. If we pick the 2kg item then we cannot pick 1kg item from the 2kg item (item is not divisible); we have to pick the 2kg item completely.
Is there a polynomial time algorithm for knapsack optimization?
Approximation Schemes. The Knapsack Problem is an NP-Hard optimization problem, which means it is unlikely that a polynomial time algorithm exists that will solve any instance of the problem.
How to solve the knapsack problem?
A Polynomial Time Approximation Scheme for the Knapsack Problem can be achieved by extending partial, small-size solutions via a greedy algorithm. A heuristic technique proposed by George Dantzig is a naive but fast approach to the Knapsack Problem.
How much can I pack in my knapsack?
Total weight of all items and bag: 9003g Maximum weight of items I can pack: 5585g Total possible worth of items: 820 The challenge: Pack as many items as the limit allows while maximizing the total worth. Before we can begin thinking about how to solve the knapsack problem, we have to solve the problem of reading in and storing our data.
How does the greedy algorithm choose the best option?
At each stage of the problem, the greedy algorithm picks the option that is locally optimal, meaning it looks like the most suitable option right now. It does not revise its previous choices as it progresses through our data set.