public NetworkSolution(AllPathFinder allPaths, Random random)
{
PathAllocations = new List <PathAllocation>();
for (var i = 0; i < allPaths.AllDemands.Count; i++)
{
PathAllocations.Add(new PathAllocation(allPaths.AllDemands[i], allPaths.AllDemands[i].PossiblePaths[random.Next(allPaths.AllDemands[i].PossiblePaths.Count)]));
}
}
public GeneticService(GeneticAlgorithmParameters parameters, Network network, AllPathFinder paths, string fileName)
{
_parameters = parameters;
_network = network;
_pathFinder = paths;
_calculator = new LambdaCalculator();
_outputWriter = new OutputWriter();
_currentFileName = fileName;
}
static void Main(string[] args)
{
InputFileParser parser = new InputFileParser();
Console.WriteLine("Choose network to optimize:");
Console.WriteLine("1: Network_1.txt");
Console.WriteLine("2: Network_2.txt");
string choice = Console.ReadLine();
Network inputNetwork = new Network();
if (choice.Equals("1") || choice.Equals("2"))
{
inputNetwork = parser.ReadNetwork("Network_" + choice + ".txt");
}
else
{
return;
}
//Find all node pairs
AllPathFinder pathFinder = new AllPathFinder();
for (int i = 1; i < inputNetwork.Nodes.Count; i++)
{
for (int j = i + 1; j < inputNetwork.Nodes.Count + 1; j++)
{
pathFinder.FindAllPaths(i, j, inputNetwork);
}
}
// all paths generated. Finding perfect combination.
GeneticAlgorithmParameters parameters = new GeneticAlgorithmParameters();
parameters.InitialPopulationSize = 100;
parameters.CrossoverProbability = (float)0.2;
parameters.MutationProbability = (float)0.1;
parameters.RandomSeed = 4253;
parameters.LimitValue = 30;
parameters.StoppingCriteria = StoppingCriteria.NoImprovement;
string fileName = "Network_" + choice;
GeneticService geneticService = new GeneticService(parameters, inputNetwork, pathFinder, fileName);
geneticService.Solve();
}