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# Fractional Knapsack Problem

Given weights and values of n items, we need to put these items in a knapsack of capacity W to get the maximum total value in the knapsack.

```
Input: 
Items as (value, weight) pairs 
arr[] = {{60, 10}, {100, 20}, {120, 30}} 
Knapsack Capacity, W = 50; 

Output: 
Maximum possible value = 240 
by taking items of weight 10 and 20 kg and 2/3 fraction 
of 30 kg. Hence total price will be 60+100+(2/3)(120) = 240
```

In **Fractional Knapsack**, we can break items for maximizing the total value of knapsack. This problem in which we can break an item is also called the fractional knapsack problem. 

```
Input : 
Same as above

Output :
Maximum possible value = 240
By taking full items of 10 kg, 20 kg and 
2/3rd of last item of 30 kg
```

A **brute-force solution** would be to try all possible subsets with all different fractions but that will be too much time taking. 

An **efficient solution** is to use the 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. 

To do that, we sort the input in descending order of the ratio.

In the above example, the order will be {{60, 10}, {100, 20}, {120, 30}} .

Then take the item with the highest ratio and add them until we can’t add them anymore. Continue the process with the next element until the Knapsack weight is reached. 

This will always be the optimal solution to this problem.