public void GetDreznerQAPInstanceTest()
{
var target = new DreznerQAPInstanceProvider();
StringBuilder erroneousInstances = new StringBuilder();
int count = 0;
foreach (var id in target.GetDataDescriptors())
{
try {
target.LoadData(id);
} catch (Exception ex) {
erroneousInstances.AppendLine(id.Name + ": " + ex.Message);
}
count++;
}
Assert.IsTrue(count > 0, "No problem instances were found.");
Assert.IsTrue(erroneousInstances.Length == 0, "Some instances could not be parsed: " + Environment.NewLine + erroneousInstances.ToString());
}
private CSharpScript CreateGAQAPScript()
{
var script = new CSharpScript {
Name = ScriptItemName,
Description = ScriptItemDescription
};
#region Variables
var provider = new DreznerQAPInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name == ProblemInstanceName);
var data = provider.LoadData(instance);
var problem = new QuadraticAssignmentProblem();
problem.Load(data);
script.VariableStore.Add(ProblemInstanceName, problem);
#endregion
#region Code
script.Code = ScriptSources.GAQAPScriptSource;
#endregion
return(script);
}
public override void Main()
{
DateTime start = DateTime.UtcNow;
QuadraticAssignmentProblem qap;
if (vars.Contains("qap"))
{
qap = vars.qap;
}
else
{
var provider = new DreznerQAPInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name == "dre56");
var data = provider.LoadData(instance);
qap = new QuadraticAssignmentProblem();
qap.Load(data);
vars.qap = qap;
}
const uint seed = 0;
const int popSize = 100;
const int generations = 1000;
const double mutationRate = 0.05;
var random = new MersenneTwister(seed);
var population = new Permutation[popSize];
var qualities = new double[popSize];
var nextGen = new Permutation[popSize];
var nextQual = new double[popSize];
var qualityChart = new DataTable("Quality Chart");
var qualityRow = new DataRow("Best Quality");
qualityChart.Rows.Add(qualityRow);
vars.qualityChart = qualityChart;
for (int i = 0; i < popSize; i++)
{
population[i] = new Permutation(PermutationTypes.Absolute, qap.Weights.Rows, random);
qualities[i] = QAPEvaluator.Apply(population[i], qap.Weights, qap.Distances);
}
var bestQuality = qualities.Min();
var bestQualityGeneration = 0;
for (int g = 0; g < generations; g++)
{
var parents = population.SampleProportional(random, 2 * popSize, qualities, windowing: true, inverseProportional: true).ToArray();
for (int i = 0; i < popSize; i++)
{
nextGen[i] = PartiallyMatchedCrossover.Apply(random, parents[i * 2], parents[i * 2 + 1]);
if (random.NextDouble() < mutationRate)
{
Swap2Manipulator.Apply(random, nextGen[i]);
}
nextQual[i] = QAPEvaluator.Apply(nextGen[i], qap.Weights, qap.Distances);
if (nextQual[i] < bestQuality)
{
bestQuality = nextQual[i];
bestQualityGeneration = g;
}
}
qualityRow.Values.Add(bestQuality);
Array.Copy(nextGen, population, popSize);
Array.Copy(nextQual, qualities, popSize);
}
vars.elapsed = new TimeSpanValue(DateTime.UtcNow - start);
vars.bestQuality = bestQuality;
vars.bestQualityFoundAt = bestQualityGeneration;
}
