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 RunSingleResearch(Landscape landscape, ResearchParameters parameters, IOperator op, string instanceId,
string inputPath, string outputPath, Action <string, float> callback, string connectionId, float step)
{
string path = outputPath + @"\" + instanceId + "_" + op.GetId() + ".csv";
if (File.Exists(path))
{
callback(connectionId, step * (parameters.RandomWalkNumber));
return;
}
StringBuilder dataBuilder = new StringBuilder();
int threadNumber = Environment.ProcessorCount;
Thread[] rwThreads = new Thread[threadNumber];
int tasksPerThread = parameters.RandomWalkNumber / threadNumber;
for (int i = 0; i < threadNumber; ++i)
{
int start = i * tasksPerThread;
int end = (i + 1) * tasksPerThread;
if (i == threadNumber - 1)
{
end += parameters.RandomWalkNumber % threadNumber;
}
rwThreads[i] = new Thread(() =>
{
DoRandomWalkThread(start, end, landscape, parameters, op,
dataBuilder, callback, connectionId, step);
});
rwThreads[i].Start();
}
foreach (Thread thread in rwThreads)
{
thread.Join();
}
File.Create(path).Close();
using (TextWriter tw = new StreamWriter(path))
{
tw.WriteLine(CSV_HEADER);
tw.Write(dataBuilder.ToString());
}
}
public void Run(ResearchParameters parameters, string inputPath, string outputPath, Action <string, float> callback, string connectionId)
{
int distanceWeight = 1;
Dictionary <string, int> customerNumbers = new Dictionary <string, int>()
{
{ "1", parameters.RoadWeight200 },
{ "2", parameters.RoadWeight200 },
//{ "4", parameters.RoadWeight400 },
//{ "6", parameters.RoadWeight600 }, { "8", parameters.RoadWeight800 },
//{ "10", parameters.RoadWeight1000 }
};
float step = 1.0f /
(CUSTOMER_TYPES.Count() * customerNumbers.Count * CUSTOMER_INSTANCES.Count() *
(parameters.CrossoverOperators.Count + parameters.MutationOperators.Count) * parameters.RandomWalkNumber);
foreach (var type in CUSTOMER_TYPES)
{
foreach (var number in customerNumbers)
{
for (int index = 0; index < CUSTOMER_INSTANCES.Count(); ++index)
{
string instanceId = type + '_' + number.Key + '_' + CUSTOMER_INSTANCES[index];
VrptwProblem problem = reader.ReadFromFile(inputPath + @"\" + instanceId + ".txt");
FitnessFunction ff = new FitnessFunction(number.Value, distanceWeight);
Landscape landscape = new Landscape(problem, factory, ff);
foreach (var op in parameters.CrossoverOperators)
{
RunSingleResearch(landscape, parameters, op, instanceId, inputPath, outputPath,
callback, connectionId, step);
}
foreach (var op in parameters.MutationOperators)
{
RunSingleResearch(landscape, parameters, op, instanceId, inputPath, outputPath,
callback, connectionId, step);
}
}
}
}
}
