private static void CompareMethods()
{
string s = "problem;method;cost\n";
foreach (string filename in vrps)
{
TSP evaluation = VRPLoader.readTSP(filename);
List <double> scores = new List <double>();
for (int i = 0; i < 100; i++)
{
scores.Add(evaluation.Evaluate(GA.GetRandomSolution(evaluation)));
}
s += filename + ";random;" + Median(scores).ToString() + "\n";
scores = new List <double>();
for (int i = 0; i < evaluation.size; i++)
{
scores.Add(evaluation.Evaluate(GreedyAlgorithm.GenerateGreedySolution(evaluation, i)));
}
s += filename + ";greedy;" + scores.Average().ToString() + "\n";
scores = new List <double>();
for (int i = 0; i < 10; i++)
{
List <int> solution;
(solution, _) = GA.Run(evaluation, 100, 100, 0.6, 0.3, 10);
scores.Add(evaluation.Evaluate(solution));
}
s += filename + ";genetic;" + Median(scores).ToString() + "\n";
}
File.WriteAllText("comparison-test.csv", s);
}
private static void TestGreedy()
{
TSP tsp = VRPLoader.readTSP(vrps[0]);
var solution = GreedyAlgorithm.GenerateGreedySolution(tsp, 0);
Console.WriteLine("Solution: " + ListToString(solution));
Console.WriteLine("Distance: " + tsp.Evaluate(solution).ToString());
}
private static void TestGA()
{
TSP tsp = VRPLoader.readTSP(vrps[0]);
List <(double, double, double)> stats;
List <int> bestSolution;
(bestSolution, stats) = GA.Run(tsp, 100, 100, 0.7, 0.1, 5);
Console.WriteLine("Solution: " + ListToString(bestSolution));
Console.WriteLine("Distance: " + tsp.Evaluate(bestSolution).ToString());
}
private static void LogStats()
{
string s = "problem;generation;best;worst;average\n";
foreach (string filename in vrps)
{
TSP evaluation = VRPLoader.readTSP(filename);
List <(double, double, double)> stats;
(_, stats) = GA.Run(evaluation, 100, 100, 0.6, 0.3, 10);
for (int i = 0; i < stats.Count; i++)
{
s += filename + ";" + i.ToString() + ";" + stats[i].Item1.ToString() + ";" + stats[i].Item2.ToString() + ";" + stats[i].Item3.ToString() + "\n";
}
}
File.WriteAllText("stats-test.csv", s);
}
