static void Main(string[] args)
{
Random rand = new Random();
int sampSize = 30;
double[,] results = new double[5, sampSize];
/*
* for (int i = 0; i < sampSize; i++)
* {
* results[0,i] = RandomSearch.Run(1000, rand);
* results[1,i] = HillClimbing.Run(1000, rand);
* results[2,i] = TabooSearch.Run(1000, rand, 4);
* GA ga = new GA(20, 10, 0.05, rand);
* results[3,i] = ga.Run(50);
* SimulatedAnnealing sa = new SimulatedAnnealing(-1, 2, 6, rand);
* results[4,i] = sa.Run(1000, 20, rand);
* }
*
* try
* {
*
* FileStream fileStream = File.Open("meta_results.txt", FileMode.Create, FileAccess.Write);
* StreamWriter fileWriter = new StreamWriter(fileStream);
* fileWriter.WriteLine("randSearch;hillClimb;taboo;ga;sa;");
*
* for (int i = 0; i < sampSize; i++)
* {
* for (int j = 0; j < 5; j++)
* {
* fileWriter.Write(results[j,i]+";");
* }
* fileWriter.WriteLine("");
* }
*
* fileWriter.Flush();
* fileWriter.Close();
* }
* catch (IOException ioe)
* {
* Console.WriteLine(ioe);
* }
*/
//TSP
Problem_TSP problem = new Problem_TSP();
problem.ReadProblem("TSP30.txt");
GA_TSP ga_tsp;
for (int i = 0; i < sampSize; i++)
{
ga_tsp = new GA_TSP(50, 0.1, 0.8, rand);
results[0, i] = ga_tsp.Run(50);
ga_tsp = new GA_TSP(50, 0.3, 0.8, rand);
results[1, i] = ga_tsp.Run(50);
ga_tsp = new GA_TSP(50, 0.1, 0.5, rand);
results[2, i] = ga_tsp.Run(50);
ga_tsp = new GA_TSP(25, 0.1, 0.8, rand);
results[3, i] = ga_tsp.Run(100);
ga_tsp = new GA_TSP(100, 0.1, 0.8, rand);
results[4, i] = ga_tsp.Run(25);
}
try
{
FileStream fileStream = File.Open("TSP_results.txt", FileMode.Create, FileAccess.Write);
StreamWriter fileWriter = new StreamWriter(fileStream);
fileWriter.WriteLine("basic;highMutProb;lowCrossProb;moreIter;bigPop;");
for (int i = 0; i < sampSize; i++)
{
for (int j = 0; j < 5; j++)
{
fileWriter.Write(results[j, i] + ";");
}
fileWriter.WriteLine("");
}
fileWriter.Flush();
fileWriter.Close();
}
catch (IOException ioe)
{
Console.WriteLine(ioe);
}
}
public void Evaluate()
{
this.fitness = Problem_TSP.Function(solution);
}
