static void Main(string[] args)
{
//FloorplanProblem problem = new FloorplanProblem(50);
//FloorplanSolution solution = new FloorplanSolution(problem);
//Swap swap = new Swap(problem.Dimension);
//Shift shift = new Shift(problem.Dimension);
//FullLeafMove leaf = new FullLeafMove(problem.Dimension);
//List<Operator> operations = new List<Operator> { swap, shift, leaf };
TspProblem problem = new TspProblem(100);
TspSolution solution = new TspSolution(problem);
Swap swap = new Swap(problem.Dimension, 1);
Shift shift = new Shift(problem.Dimension, 2);
TwoOpt twoOpt = new TwoOpt(problem.Dimension, 3);
List <Operator> operations = new List <Operator> {
swap, shift, twoOpt
};
MultistartParameters multistartOptions = new MultistartParameters()
{
InstancesNumber = 1,
OutputFrequency = 500,
};
LocalDescentParameters ldParameters = new LocalDescentParameters()
{
DetailedOutput = true,
Seed = 0,
Operators = operations,
IsSteepestDescent = false
};
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters()
{
InitProbability = 0.3,
TemperatureCooling = 0.97,
UseWeightedNeighborhood = true,
DetailedOutput = false,
Seed = 0,
Operators = operations,
};
MultistartParameters ldMultistartParameters = (MultistartParameters)multistartOptions.Clone();
ldMultistartParameters.Parameters = ldParameters;
MultistartParameters saMultistartParameters = (MultistartParameters)multistartOptions.Clone();
saMultistartParameters.Parameters = saParameters;
LocalDescent ld = new LocalDescent(ldParameters);
SimulatedAnnealing sa = new SimulatedAnnealing(saParameters);
ParallelMultistart pld = new ParallelMultistart(ldMultistartParameters);
ParallelMultistart psa = new ParallelMultistart(saMultistartParameters);
List <string> operators = new List <string>();
IPermutation sol = solution;
foreach (IPermutation s in ld.Minimize(solution))
{
Console.WriteLine("{0}, {1:f}s, {2}, {3}, {4}, {5}", s.CostValue, s.TimeInSeconds, s.IterationNumber, s.IsCurrentBest, s.IsFinal, sol.CostValue - s.CostValue);
sol = s;
operators.Add(s.OperatorTag);
}
//var groups = operators.GroupBy(s => s).Select(s => new { Operator = s.Key, Count = s.Count() });
//var dictionary = groups.ToDictionary(g => g.Operator, g => g.Count);
//foreach (var o in groups)
//{
// Console.WriteLine("{0} = {1}", o.Operator, o.Count);
//}
Console.WriteLine("Done");
Console.ReadLine();
}
private void bwTsp_DoWork(object sender, DoWorkEventArgs e)
{
BackgroundWorker worker = (BackgroundWorker)sender;
algorithmStatus.Text = "Press ESC to cancel";
TspProblem problem = new TspProblem(tspCities);
TspSolution startSolution = new TspSolution(problem);
Swap swap = new Swap(problem.Dimension, 1);
Shift shift = new Shift(problem.Dimension, 2);
TwoOpt twoOpt = new TwoOpt(problem.Dimension, 3);
List <Operator> operations = new List <Operator> {
swap, shift, twoOpt
};
MultistartParameters multistartParameters = (MultistartParameters)multistartOptions.Clone();
LocalDescentParameters ldParameters = new LocalDescentParameters()
{
Name = "TSP LD",
Seed = seed,
DetailedOutput = true,
Operators = operations
};
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters()
{
Name = "TSP SA",
InitProbability = 0.5,
TemperatureCooling = 0.91,
MinCostDeviation = 10E-3,
Seed = seed,
DetailedOutput = true,
Operators = operations
};
StackedParameters ssParameters = new StackedParameters()
{
Name = "B",
DetailedOutput = true,
OptimizationAlgorithms = new Type[] { typeof(LocalDescent), typeof(SimulatedAnnealing), typeof(LocalDescent) },
Parameters = new OptimizationParameters[] { ldParameters, saParameters, ldParameters }
};
switch (optimizerType)
{
case 0:
{
multistartParameters.Parameters = ldParameters;
multistartParameters.OptimizationAlgorithm = typeof(LocalDescent);
}
break;
case 1:
{
multistartParameters.Parameters = saParameters;
multistartParameters.OptimizationAlgorithm = typeof(SimulatedAnnealing);
}
break;
case 2:
{
saParameters.InitProbability = 0.007;
saParameters.MinCostDeviation = 10E-2;
multistartParameters.Parameters = ssParameters;
multistartParameters.OptimizationAlgorithm = typeof(StackedSearch);
}
break;
case 3:
{
saParameters.InitProbability = 0.007;
saParameters.MinCostDeviation = 10E-2;
multistartParameters.InstancesNumber = 3;
multistartParameters.Parameters = ssParameters;
multistartParameters.OptimizationAlgorithm = typeof(StackedSearch);
}
break;
}
tspOptimizer = new ParallelMultistart(multistartParameters);
toRenderBackground = false;
foreach (ISolution solution in tspOptimizer.Minimize(startSolution))
{
if (worker.CancellationPending)
{
tspOptimizer.Stop();
e.Cancel = true;
}
if (e.Cancel)
{
solution.IsFinal = false;
}
worker.ReportProgress(0);
}
}