0-1 Knapsack algorithm

前端 未结 6 2094
花落未央
花落未央 2021-02-09 12:35

Is the following 0-1 Knapsack problem solvable:

  • \'float\' positive values and
  • \'float\' weights (can be positive or negative)
  • \'float\' capacity
6条回答
  •  清歌不尽
    2021-02-09 12:59

    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;
        }
    }
    

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