public void Start()
{
RandomizeLocations();
State alpha = new State();
alpha.AddCityToPath(SearchInfo.AllCities[0]);
switch ((Algorithm)method)
{
case Algorithm.BruteForceDSF:
{
tspAlg = new BruteForceDFS_TSPAlgorithm(SearchInfo, DrawingBoard);
break;
}
case Algorithm.BruteForceBSF:
{
tspAlg = new BruteForceBFS_TSPAlgorithm(SearchInfo, DrawingBoard);
break;
}
case Algorithm.GreedyAlgorithm:
{
tspAlg = new TSPGreedyAlgorithm(SearchInfo, DrawingBoard);
break;
}
case Algorithm.GeneticAlgorithm:
{
tspAlg = new TSPGeneticAlgorithm(SearchInfo, DrawingBoard);
break;
}
}
states = tspAlg.ChildStates(alpha);
}
public AlgorithmExecutor(TSPAlgorithm algorithm, int numberOfExecutions)
{
NumberOfExecutions = numberOfExecutions;
ArrayOfBestResults = new double[numberOfExecutions];
Algorithm = algorithm;
Informations.AppendLine(algorithm.GetInformations());
AlgorithmStatistics = new double[numberOfExecutions][];
}
static void Main(string[] args)
{
int populationSize = 10;
int numberOfEpoch = 50;
int numberOfExecution = 1;
double probabilityOfMutation = 0.1;
string file = @"WesternSahara.txt";
Cities testCities = new Cities(file);
IParentSelection parentSelection = new TournamentSelection();
ICrossover crossover = new PMX();
IMutation mutation = new InsertionMutation(probabilityOfMutation);
string filename = DateTime.Now.ToString("yyyy-MM-dd HH;mm");
//Test 1 - PMX
TSPAlgorithm tsp = new TSPAlgorithm(numberOfEpoch, populationSize, testCities, parentSelection, mutation, crossover);
AlgorithmExecutor AE = new AlgorithmExecutor(tsp, numberOfExecution);
AE.Start();
AE.SaveInformations(filename + ".txt");
//AE.ExportStatisticsToCsv(filename + "_stats.csv");
/* Test 2 - CX
* crossover = new CX();
* tsp = new TSPAlgorithm(numberOfEpoch, populationSize, testCities, parentSelection, mutation, crossover);
* AE = new AlgorithmExecutor(tsp, numberOfExecution);
* AE.Start();
* AE.SaveInformations(filename + ".txt");
* AE.ExportStatisticsToCsv(filename + "_stats.csv");
*
* // Test 3 - OX
* crossover = new OX();
* tsp = new TSPAlgorithm(numberOfEpoch, populationSize, testCities, parentSelection, mutation, crossover);
* AE = new AlgorithmExecutor(tsp, numberOfExecution);
* AE.Start();
* AE.SaveInformations(filename + ".txt");
* AE.ExportStatisticsToCsv(filename + "_stats.csv");
*
* // Test 4 - AEX
* crossover = new AEX();
* tsp = new TSPAlgorithm(numberOfEpoch, populationSize, testCities, parentSelection, mutation, crossover);
* AE = new AlgorithmExecutor(tsp, numberOfExecution);
* AE.Start();
* AE.SaveInformations(filename + ".txt");
* AE.ExportStatisticsToCsv(filename + "_stats.csv");
*
* // Test 5 - SCC
* crossover = new SCC();
* tsp = new TSPAlgorithm(numberOfEpoch, populationSize, testCities, parentSelection, mutation, crossover);
* AE = new AlgorithmExecutor(tsp, numberOfExecution);
* AE.Start();
* AE.SaveInformations(filename + ".txt");
* AE.ExportStatisticsToCsv(filename + "_stats.csv");
*
* //Test 6 - SCC
* crossover = new ClassicalCrossover();
* mutation = new ClassicMutationInOrdinalRepresentation(probabilityOfMutation);
* tsp = new TSPAlgorithm(numberOfEpoch, populationSize, testCities, parentSelection, mutation, crossover);
* AE = new AlgorithmExecutor(tsp, numberOfExecution);
* AE.Start();
* //AE.SaveInformations(filename + ".txt");
* //AE.ExportStatisticsToCsv(filename + "_stats.csv");
*/
Console.ReadKey();
}
