Reputation: 134
Is there a algorithm to determine a knapsack which has an exact weight W? I.e. it's like the normal 0/1 knapsack problem with n items each having weight w_i and value v_i. Maximise the value of all the items, however the total weight of the items in the knapsack need to have exactly weight W!
I know the "normal" 0/1 knapsack algorithm but this could also return a knapsack with less weight but higher value. I want to find the highest value but exact W weight.
Here is my 0/1 knapsack implementation:
public class KnapSackTest {
public static void main(String[] args) {
int[] w = new int[] {4, 1, 5, 8, 3, 9, 2}; //weights
int[] v = new int[] {2, 12, 8, 9, 3, 4, 3}; //values
int n = w.length;
int W = 15; // W (max weight)
int[][] DP = new int[n+1][W+1];
for(int i = 1; i < n+1; i++) {
for(int j = 0; j < W+1; j++) {
if(i == 0 || j == 0) {
DP[i][j] = 0;
} else if (j - w[i-1] >= 0) {
DP[i][j] = Math.max(DP[i-1][j], DP[i-1][j - w[i-1]] + v[i-1]);
} else {
DP[i][j] = DP[i-1][j];
}
}
}
System.out.println("Result: " + DP[n][W]);
}
}
This gives me:
Result: 29
(Just ask if anything is unclear in my question!)
Upvotes: 5
Views: 4797
Reputation: 1848
Actually, the accepted answer is wrong, as found by @Shinchan in the comments.
You get exact weight knapsack by changing only the initial dp
state, not the algorithm itself.
The initialization, instead of:
if(i == 0 || j == 0) {
DP[i][j] = 0;
}
should be:
if (j == 0) {
DP[i][j] = 0;
} else if (i == 0 && j > 0) { // obviously `&& j > 0` is not needed, but for clarity
DP[i][j] = -inf;
}
The rest stays as in your question.
Upvotes: 5
Reputation: 178451
By simply setting DP[i][j] = -infinity
in your last else
clause it will do the trick.
The ides behind it is to slightly change the recursive formula definition to calculate:
j
up to item i
.Now, the induction hypothesis will change, and the proof of correctness will be very similar to regular knapsack with the following modification:
DP[i][j-weight[i]] is now the maximal value that can be constructed with exactly j-weight[i]
, and you can either take item i
, giving value of DP[i][j-weight[i]]
, or not taking it, giving value of DP[i-1][j]
- which is the maximal value when using exactly weight j
with first i-1
items.
Note that if for some reason you cannot construct DP[i][j]
, you will never use it, as the value -infinity will always discarded when looking for MAX.
Upvotes: 2