static void Main(string[] args)
{
string path = Directory.GetCurrentDirectory();
InputProcessor inputprocessor = new InputProcessor(Path.Combine(path, @"..\..\..\", @"AfstandenMatrix.txt"), Path.Combine(path, @"..\..\..\", @"Orderbestand.txt"));
//Console.WriteLine(inputprocessor.order_dict[-2].matrixID);
ScoreCalculator scorecalculator = new ScoreCalculator(inputprocessor.afstanden_dict, inputprocessor.order_dict);
LocalSearcher localsearcher = new LocalSearcher();
Oplossing sample = new Oplossing();
sample.vrachtwagen2[0].AddAfter(sample.vrachtwagen2[0].First, 18);
Console.WriteLine(scorecalculator.Calculate(sample));
Console.ReadLine();
}
static void Main(string[] args)
{
InputProcessor inputprocessor = new InputProcessor(@"C:\Users\laars\OneDrive\Universiteit Utrecht\2019 - Kunstmatige Intelligentie\Blok 2\Optimalisering en complexiteit\Grote opdracht\Grote Opdracht\AfstandenMatrix.txt",
@"C:\Users\laars\OneDrive\Universiteit Utrecht\2019 - Kunstmatige Intelligentie\Blok 2\Optimalisering en complexiteit\Grote opdracht\Grote Opdracht\Orderbestand.txt");
ScoreCalculator scorecalculator = new ScoreCalculator(inputprocessor.reistijden);
LocalSearcher localsearcher = new LocalSearcher();
Oplossing sample = new Oplossing();
Order k = inputprocessor.order_dict[18];
sample.vrachtwagen1[0].AddAfter(sample.vrachtwagen1[0].First, new Bezoek(18, k.aant * k.volume, k.MID, k.duur, k.aant * k.volume));
Console.WriteLine(scorecalculator.Calculate(sample, inputprocessor.order_dict));
Console.ReadLine();
}
