public void DoRandomWalkThread(int start, int end, Landscape landscape, ResearchParameters parameters, IOperator op,
StringBuilder dataBuilder, Action <string, float> callback, string connectionId, float step)
{
for (int j = start; j < end; ++j)
{
var rwResult = landscape.RandomWalk(parameters.RandomWalkSteps, op);
float ac = Autocorrelation.Run(rwResult);
float ic = InformationContent.Run(rwResult, parameters.Sensitivity);
float pic = PartialInformationContent.Run(rwResult, parameters.Sensitivity);
float dbi = DensityBasinInformation.Run(rwResult, parameters.Sensitivity);
string line =
(float.IsNaN(ac) ? FLOAT_PATTERN : ac.ToString(FLOAT_PATTERN)) + SEPARATOR +
(float.IsNaN(ic) ? FLOAT_PATTERN : ic.ToString(FLOAT_PATTERN)) + SEPARATOR +
(float.IsNaN(pic) ? FLOAT_PATTERN : pic.ToString(FLOAT_PATTERN)) + SEPARATOR +
(float.IsNaN(dbi) ? FLOAT_PATTERN : dbi.ToString(FLOAT_PATTERN));
dataBuilder.AppendLine(line);
callback(connectionId, step);
}
}
public void Test1()
{
AbstractChromosomeFactory factory = new SolutionFactory();
int[] routeWeights = new int[]
{
20000, 50000, 120000, 200000, 350000
};
int distanceWeight = 1;
string[] customerTypes = new string[] { "C1", "C2", "R1", "R2", "RC1", "RC2" };
Dictionary <string, int> customerNumbers = new Dictionary <string, int>()
{
{ "2", 20000 }, { "4", 50000 }, { "6", 120000 }, { "8", 200000 }, { "10", 350000 }
};
string[] customerInstances = new string[] { "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" };
CrossoverOperator[] crossoverOps = new CrossoverOperator[]
{
new OrderCrossover(), new PartiallyMatchedCrossover(), new CycleCrossover(), new UniformBasedOrderCrossover()
};
MutationOperator[] mutationOps = new MutationOperator[]
{
new SwapOperator(), new InsertionOperator(), new InversionOperator(), new DisplacementOperator()
};
int randomWalkNumber = 2000, randomWalkSteps = 5000;
string floatPattern = "0.000", separator = ",";
float epsilon = 0.05f;
foreach (var type in customerTypes)
{
foreach (var number in customerNumbers)
{
foreach (var instance in customerInstances)
{
string instanceId = type + '_' + number.Key + '_' + instance;
VrptwProblem problem = reader.ReadFromFile(FILE_PATH + @"\" + instanceId + ".txt");
FitnessFunction ff = new FitnessFunction(number.Value, distanceWeight);
Landscape landscape = new Landscape(problem, factory, ff);
foreach (var op in crossoverOps)
{
string path = RESULT_PATH + @"\" + instanceId + "_" + op.GetId() + ".csv";
if (!File.Exists(path))
{
File.Create(path).Close();
File.ReadAllText(path);
using (TextWriter tw = new StreamWriter(path))
{
tw.WriteLine("AC, IC, PIC, DBI");
for (int i = 0; i < randomWalkNumber; ++i)
{
var rwResult = landscape.RandomWalk(randomWalkSteps, op);
float ac = Autocorrelation.Run(rwResult);
float ic = InformationContent.Run(rwResult, epsilon);
float pic = PartialInformationContent.Run(rwResult, epsilon);
float dbi = DensityBasinInformation.Run(rwResult, epsilon);
string line =
ac.ToString(floatPattern) + separator +
ic.ToString(floatPattern) + separator +
pic.ToString(floatPattern) + separator +
dbi.ToString(floatPattern);
tw.WriteLine(line);
}
}
}
}
}
}
}
}