Exemplo n.º 1
0
        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)]));
            }
        }
Exemplo n.º 2
0
 public GeneticService(GeneticAlgorithmParameters parameters, Network network, AllPathFinder paths, string fileName)
 {
     _parameters      = parameters;
     _network         = network;
     _pathFinder      = paths;
     _calculator      = new LambdaCalculator();
     _outputWriter    = new OutputWriter();
     _currentFileName = fileName;
 }
Exemplo n.º 3
0
        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();
        }