public static async Task <Chromosome> DoMa(string filename, CrossoverOperator crossOp, MutationOperator mutOp)
{
var problem = new VrptwProblemReader().ReadFromFile(filename);
var parameters = new Parameters()
{
ChromosomeFactory = new SolutionFactory(),
ConvergenceLimit = 0.15f,
CrossoverOperators = new List <CrossoverOperator> {
crossOp
},
CrossoverProbability = 0.9f,
EliteChildrenCount = 4,
Fitness = new FitnessFunction(200000, 1),
FitnessStrategy = FitnessStrategy.MINIMIZE,
GeneCount = problem.GeneCount(),
Heuristics = new SimulatedAnnealing(),
HeuristicsParameters = new float[] { 100, 0.90f, 50 },
MaxIterations = 300,
MutationOperators = new List <MutationOperator> {
mutOp
},
MutationProbability = 0.15f,
PopulationSize = 200,
PreservedChromosomesNumber = 4,
Selection = new TournamentSelection()
};
MemeticAlgorithm ma = new MemeticAlgorithm();
Chromosome sol = await ma.Run(problem, parameters, CallBackMa, crossOp.GetId() + "-" + mutOp.GetId());
return(sol);
}
public void RegisterAlgorithm(string problemName, ParametersWebsite webParameters)
{
string filePath = HttpContext.Current.Server.MapPath("~/Data/Homberger/" + problemName.ToUpper() + @".txt");
VrptwProblem problem = new VrptwProblemReader().ReadFromFile(filePath);
string connecionId = Context.ConnectionId;
Register();
MemeticAlgorithm ma;
if (algorithms.ContainsKey(connecionId))
{
ma = algorithms[connecionId];
ma.Stop();
}
else
{
ma = new MemeticAlgorithm();
}
Parameters parameters = new Parameters
{
Heuristics = HeuristicsFactory.Create(webParameters.Heuristics),
PopulationSize = webParameters.PopulationSize,
Selection = SelectionFactory.Create(webParameters.Selection),
CrossoverOperators = new List <CrossoverOperator>(),
MutationOperators = new List <MutationOperator>(),
CrossoverProbability = webParameters.CrossoverProbability,
MutationProbability = webParameters.MutationProbability,
Fitness = new FitnessFunction(webParameters.FitnessRoutes, webParameters.FitnesDistance),
EliteChildrenCount = webParameters.EliteChildrenCount,
GeneCount = problem.Customers.Count,
FitnessStrategy = FitnessStrategy.MINIMIZE,
ConvergenceLimit = webParameters.ConvergenceLimit,
PreservedChromosomesNumber = webParameters.PreservedChromosomeNumber,
MaxIterations = webParameters.Iterations,
ChromosomeFactory = new SolutionFactory(),
HeuristicsParameters = webParameters.HeuristicsParameters
};
parameters.CrossoverOperators.Add(CrossoverOperatorFactory.Create(webParameters.Crossover));
parameters.MutationOperators.Add(MutationOperatorFactory.Create(webParameters.Mutation));
algorithms.TryAdd(connecionId, ma);
var result = ma.Run(problem, parameters, UpdateSolution, connecionId);
var solution = result.Result as Solution;
string outputPath = HttpContext.Current.Server.MapPath("~/Results/Memetic");
string outputFilePath = outputPath + @"/" + problem.Name + ".txt";
File.WriteAllText(outputFilePath, solution.ToFileText());
}
public void Setup()
{
reader = new VrptwProblemReader();
}
public void SetUp()
{
reader = new VrptwProblemReader();
problem = reader.ReadFromFile(FILE_PATH);
}
public void SetUp()
{
reader = new VrptwProblemReader();
factory = new SolutionFactory();
fitness = new FitnessFunction(5000, 1);
}
