public static FindMethod ReadSolutionResourceOrFindSolutionEnd(string line, KnapsackProblemDataParser data)
{
if (string.IsNullOrWhiteSpace(line))
{
return(null);
}
var parts = line.Split('\t').Where(s => !string.IsNullOrWhiteSpace(s)).Select(p => p).ToArray();
var resourceIndex = int.Parse(parts[0]) - 1;
var resourceQuantity = int.Parse(parts[1]);
var item = new ItemQuantity(data.Resources[resourceIndex], resourceQuantity);
data.Solution.Add(item);
return(ReadSolutionResourceOrFindSolutionEnd);
}
public void LoadDataTest()
{
var problemInfo = KnapsackProblemDataParser.LoadData(@"..\..\Data\exnsd16.ukp");
Assert.AreEqual(889304, problemInfo.MaxWeight);
Assert.AreEqual(2000, problemInfo.Resources.Length);
Assert.AreEqual(2, problemInfo.Solution.Length);
// nb idx w p
// 156 x R288, 5687, 0, 6585
// 1 x R987, 2131, 0, 2420
var iq1 = new ItemQuantity(problemInfo.Resources[288 - 1], 156);
var iq2 = new ItemQuantity(problemInfo.Resources[987 - 1], 1);
CollectionAssert.AreEquivalent(new[] { iq1, iq2 }, problemInfo.Solution);
}
private static void Mutate(IList <ItemQuantity> genes, IList <Resource> items, double maxWeight, double maxVolume,
Window window)
{
window.Slide();
var fitness = GetFitness(genes);
var remainingWeight = maxWeight - fitness.TotalWeight;
var remainingVolume = maxVolume - fitness.TotalVolume;
var removing = genes.Count > 1 && Rand.PercentChance(10);
if (removing)
{
var index1 = Rand.Random.Next(genes.Count);
var iq1 = genes[index1];
var item1 = iq1.Item;
remainingWeight += item1.Weight * iq1.Quantity;
remainingVolume += item1.Volume * iq1.Quantity;
genes.RemoveAt(index1);
}
var adding = (remainingWeight > 0 || remainingVolume > 0) &&
(genes.Count == 0 || (genes.Count < items.Count && Rand.PercentChance(1)));
if (adding)
{
var newGene = Add(genes, items, remainingWeight, remainingVolume);
if (newGene != null)
{
genes.Add(newGene);
return;
}
}
var index = Rand.Random.Next(genes.Count);
var iq = genes[index];
var item = iq.Item;
remainingWeight += item.Weight * iq.Quantity;
remainingVolume += item.Volume * iq.Quantity;
var changeItem = genes.Count < items.Count && Rand.PercentChance(25);
if (changeItem)
{
var itemIndex = items.IndexOf(iq.Item);
var start = Math.Max(1, itemIndex - window.Size);
var stop = Math.Min(items.Count - 1, itemIndex + window.Size);
item = items[Rand.Random.Next(start, stop)];
}
var maxQuantity = MaxQuantity(item, remainingWeight, remainingVolume);
if (maxQuantity > 0)
{
var newGene = new ItemQuantity(item, window.Size > 1 ? maxQuantity : Rand.Random.Next(1, maxQuantity));
genes[index] = newGene;
}
else
{
genes.RemoveAt(index);
}
}
