0-1 Knapsack algorithm

alhazen picture alhazen · Nov 14, 2011 · Viewed 13.7k times · Source

Is the following 0-1 Knapsack problem solvable:

  • 'float' positive values and
  • 'float' weights (can be positive or negative)
  • 'float' capacity of the knapsack > 0

I have on average < 10 items, so I'm thinking of using a brute force implementation. However, I was wondering if there is a better way of doing it.

Answer

Ben Voigt picture Ben Voigt · Nov 14, 2011

This is a relatively simple binary program.

I'd suggest brute force with pruning. If at any time you exceed the allowable weight, you don't need to try combinations of additional items, you can discard the whole tree.

Oh wait, you have negative weights? Include all negative weights always, then proceed as above for the positive weights. Or do the negative weight items also have negative value?

Include all negative weight items with positive value. Exclude all items with positive weight and negative value.

For negative weight items with negative value, subtract their weight (increasing the knapsack capavity) and use a pseudo-item which represents not taking that item. The pseudo-item will have positive weight and value. Proceed by brute force with pruning.

class Knapsack
{
    double bestValue;
    bool[] bestItems;
    double[] itemValues;
    double[] itemWeights;
    double weightLimit;

    void SolveRecursive( bool[] chosen, int depth, double currentWeight, double currentValue, double remainingValue )
    {
        if (currentWeight > weightLimit) return;
        if (currentValue + remainingValue < bestValue) return;
        if (depth == chosen.Length) {
            bestValue = currentValue;
            System.Array.Copy(chosen, bestItems, chosen.Length);
            return;
        }
        remainingValue -= itemValues[depth];
        chosen[depth] = false;
        SolveRecursive(chosen, depth+1, currentWeight, currentValue, remainingValue);
        chosen[depth] = true;
        currentWeight += itemWeights[depth];
        currentValue += itemValues[depth];
        SolveRecursive(chosen, depth+1, currentWeight, currentValue, remainingValue);
    }

    public bool[] Solve()
    {
        var chosen = new bool[itemWeights.Length];
        bestItems = new bool[itemWeights.Length];
        bestValue = 0.0;
        double totalValue = 0.0;
        foreach (var v in itemValues) totalValue += v;
        SolveRecursive(chosen, 0, 0.0, 0.0, totalValue);
        return bestItems;
    }
}