public IHarmonySearcher <StopTimeInfo> GetHarmonySearcher(Graph <int, StopTimeInfo> graph, Location source, Location destination)
{
var objectiveFunction = ObjectiveFunctionFactory.GetInstance(ObjectiveFunctionType, destination);
var harmonyGenerator = HarmonyGeneratorFactory.GetInstance(HarmonyGeneratorType, objectiveFunction, graph, source, destination);
var antColonyOptimizer = new StopTimeAntColonyOptimizer(objectiveFunction, graph, source, destination);
var harmonySearcher = HarmonySearcherFactory.GetInstance(HarmonySearcherType, harmonyGenerator,
HarmonyMemorySize, MaxImprovisationCount, HarmonyMemoryConsiderationRatio, PitchAdjustingRatio, MinPitchAdjustingRatio, MaxPitchAdjustingRatio, antColonyOptimizer);
return(harmonySearcher);
}
public IObjectiveFunctionFactory CreateObjectiveFunctionFactory()
{
IObjectiveFunctionFactory factory = null;
try
{
factory = new ObjectiveFunctionFactory();
}
catch (Exception exception)
{
this.Log.Error("Exception message: " + exception.Message + " and stacktrace " + exception.StackTrace);
}
return(factory);
}
public IObjectiveFunctionFactory CreateObjectiveFunctionFactory()
{
IObjectiveFunctionFactory factory = null;
try
{
factory = new ObjectiveFunctionFactory();
}
catch (Exception exception)
{
this.Log.Error(
exception.Message,
exception);
}
return(factory);
}
public static void Example1()
{
TestModels.IModel modelFactory = TestModels.ModelFactory.Model2B();
XmlFilePath structureFile = modelFactory.Model();
DelimitedFilePath dataFile = modelFactory.Data();
// Read in the model and the data.
XElement model =
XElement.Load(structureFile)
.DefineAttributeData(dataFile);
// Create the objective function.
double ObjectiveFunction(double[] x)
{
XElement localModel = new XElement(model);
localModel.SetConsumerPrices(x)
.ShockProducerPrices()
.CalculateMarketShares()
.CalculateMarketEquilibrium();
return(ObjectiveFunctionFactory.SumOfSquares(localModel));
}
// Set up the simplex solver.
Simplex simplex =
new Simplex(
objectiveFunction: ObjectiveFunction,
lowerBound: 0,
upperBound: 10,
//dimensions: model.DescendantsAndSelf().Count(),
dimensions: model.DescendantsAndSelf().Count(x => !x.HasElements),
iterations: 50000,
seed: 0,
textWriter: Console.Out
);
// Find the minimum solution.
Solution solution = simplex.Minimize();
// Apply the final solution
model.SetConsumerPrices(solution.Vector)
.ShockProducerPrices()
.CalculateMarketShares()
.CalculateMarketEquilibrium();
// Print the results
PrintResults(model, solution);
//// Set up the swarm solver.
//PSO.Swarm swarm =
// new PSO.Swarm(
// objectiveFunction: x => objectiveFunction(x),
// lowerBound: 0,
// upperBound: 5,
// dimensions: model.DescendantsAndSelf().Count(x => !x.HasElements),
// iterations: 25000,
// particles: model.DescendantsAndSelf().Count(x => !x.HasElements) * 2,
// seed: 0,
// textWriter: Console.Out
// );
//// Find the minimum solution.
//Solution solution = PSO.MinimizeSwarmExtensions.Minimize(swarm);
//// Apply the final solution
//model.SetConsumerPrices(solution.Vector)
// .ShockProducerPrices()
// .CalculateMarketShares()
// .CalculateMarketEquilibrium();
//// Print the results
//PrintResults(model, solution);
}
