public RouteSet BasicPenalization(RouteSet initial, Exploration expCondition, Random rdObj, double overloadFactor,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
double saProbability, double saWorst, int saRepetitions, double saFactor, double saCoolingRate, int saCoolerAmount)
{
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters(GetCost(initial), saProbability, saWorst, saRepetitions, saFactor, saCoolingRate, saCoolerAmount);
return(BasicPenalization(initial, expCondition, rdObj, overloadFactor, neighborhoods, saParameters));
}
public RouteSet MutiStartParallelShakingPenalization(List <RouteSet> initialPool, int reStarts, Exploration expCondition, Random rdObj, double overloadFactor,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
List <Func <RouteSet, Random, RouteSet> > shaking,
SimulatedAnnealingParameters saParameters)
{
SimulatedAnnealingProcedure <RouteSet> saProcedure = new SimulatedAnnealingProcedure <RouteSet>();
return(MultiStartParallelShakingPenalization(reStarts, expCondition, rdObj, overloadFactor, neighborhoods, shaking, saProcedure, saParameters, initialPool, false));
}
public RouteSet BasicPenalization(RouteSet initial, Exploration expCondition, Random rdObj, double overloadFactor,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
SimulatedAnnealingParameters saParameters)
{
OverloadFactor = overloadFactor;
SimulatedAnnealingProcedure <RouteSet> saProcedure = new SimulatedAnnealingProcedure <RouteSet>();
return(saProcedure.Solve(saParameters, initial, neighborhoods, expCondition, GetCost, rdObj));
}
public List <RouteSet> BuildSolutionPool(double alphaStep, int alphaPool, double overloadFactor, int shakings,
Exploration expCondition, Random rdObj,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
List <Func <RouteSet, Random, RouteSet> > shakingProcedures,
SimulatedAnnealingParameters saParams)
{
SimulatedAnnealingProcedure <RouteSet> saProcedure = new SimulatedAnnealingProcedure <RouteSet>();
return(BuildSolutionPool(alphaStep, alphaPool, overloadFactor, shakings, expCondition, rdObj, neighborhoods, shakingProcedures, saProcedure, saParams));
}
public RouteSet Solve(double alphaStep, int alphaPool, double overloadFactor, int shakings,
Exploration expCondition, Random rdObj,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
List <Func <RouteSet, Random, RouteSet> > shakingProcedures,
string gamsFolderPath, SimulatedAnnealingParameters saParams)
{
SimulatedAnnealingProcedure <RouteSet> procedure = new SimulatedAnnealingProcedure <RouteSet>();
return(Solve(alphaStep, alphaPool, overloadFactor, shakings, expCondition, rdObj, neighborhoods, shakingProcedures, gamsFolderPath, procedure, saParams));
}
public RouteSet ShakingPenalization(RouteSet initial, int reStarts, Exploration expCondition, Random rdObj, double overloadFactor,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
List <Func <RouteSet, Random, RouteSet> > shaking,
SimulatedAnnealingParameters saParameters)
{
SimulatedAnnealingProcedure <RouteSet> saProcedure = new SimulatedAnnealingProcedure <RouteSet>();
return(ShakingPenalization(initial, reStarts, expCondition, rdObj, overloadFactor,
neighborhoods, shaking, saProcedure, saParameters));
}
public RouteSet MultiStartPenalization(List <RouteSet> initialPool, Exploration expCondition, Random rdObj, double overloadFactor,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
double saProbability, double saWorst, int saRepetitions, double saFactor, double saCoolingRate, int saCoolerAmount)
{
OverloadFactor = overloadFactor;
SimulatedAnnealingParameters saParameters = ComputeSAParameters(saProbability, saWorst, saRepetitions, saFactor, saCoolingRate, saCoolerAmount, initialPool);
SimulatedAnnealingProcedure <RouteSet> saProcedure = new SimulatedAnnealingProcedure <RouteSet>();
return(MultiStartPenalization(expCondition, rdObj, overloadFactor, neighborhoods, saProcedure, saParameters, initialPool));
}
public RouteSet ParallelShakingPenalization(RouteSet initial, int reStarts, Exploration expCondition, Random rdObj, double overloadFactor,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
List <Func <RouteSet, Random, RouteSet> > shaking,
double saProbability, double saWorst, int saRepetitions, double saFactor, double saCoolingRate, int saCoolerAmount)
{
SimulatedAnnealingProcedure <RouteSet> saProcedure = new SimulatedAnnealingProcedure <RouteSet>();
OverloadFactor = overloadFactor;
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters(GetCost(initial), saProbability, saWorst, saRepetitions, saFactor, saCoolingRate, saCoolerAmount);
return(ParallelShakingPenalization(initial, reStarts, expCondition, rdObj, overloadFactor,
neighborhoods, shaking, saProcedure, saParameters, false));
}
protected SimulatedAnnealingParameters ComputeSAParameters(double saProbability, double saWorst, int saRepetitions, double saFactor, double saCoolingRate, int saCoolerAmount, List <RouteSet> initialPool)
{
List <double> tmp0 = new List <double>();
List <double> tmpn = new List <double>();
foreach (var item in initialPool)
{
double t0 = SimulatedAnnealingParameters.ComputeInitialTemperature(GetCost(item), saProbability, saWorst);
tmp0.Add(t0);
tmpn.Add(SimulatedAnnealingParameters.ComputeFinalTemperature(t0, saCoolingRate, saCoolerAmount));
}
return(new SimulatedAnnealingParameters(tmp0.Average(), tmpn.Average(), saRepetitions, saFactor, saCoolingRate));
}
public RouteSet Solve(double alphaStep, int alphaPool, double overloadFactor, int shakings,
Exploration expCondition, Random rdObj,
List <Func <RouteSet, Exploration, Random, RouteSet> > neighborhoods,
List <Func <RouteSet, Random, RouteSet> > shakingProcedures,
string gamsFolderPath,
double saProbability, double saWorst, int saRepetitions, double saFactor, double saCoolingRate, int saCoolerAmount)
{
OverloadFactor = 0;
List <RouteSet> initialPool = BuildInitialPool(alphaStep, alphaPool, rdObj);
SimulatedAnnealingProcedure <RouteSet> procedure = new SimulatedAnnealingProcedure <RouteSet>();
SimulatedAnnealingParameters saParams = ComputeSAParameters(saProbability, saWorst, saRepetitions, saFactor, saCoolingRate, saCoolerAmount, initialPool);
return(Solve(overloadFactor, shakings, expCondition, rdObj, neighborhoods, shakingProcedures, gamsFolderPath, procedure, saParams, initialPool));
}
private void bwVehicleRouting_DoWork(object sender, DoWorkEventArgs e)
{
BackgroundWorker worker = (BackgroundWorker)sender;
algorithmStatus.Text = "Press ESC to cancel";
VehicleRoutingProblem problem = new VehicleRoutingProblem(routingCustomers, routingVehicles);
VehicleRoutingSolution startSolution = new VehicleRoutingSolution(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 = "VEHICLE LD",
Seed = seed,
DetailedOutput = true,
Operators = operations
};
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters()
{
Name = "VEHICLE SA",
InitProbability = 0.4,
TemperatureCooling = 0.95,
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 = 0.002;
saParameters.MinCostDeviation = 10E-2;
multistartParameters.Parameters = ssParameters;
multistartParameters.OptimizationAlgorithm = typeof(StackedSearch);
}
break;
case 3:
{
saParameters.InitProbability = 0.01;
saParameters.MinCostDeviation = 10E-2;
multistartParameters.InstancesNumber = 3;
multistartParameters.Parameters = ssParameters;
multistartParameters.OptimizationAlgorithm = typeof(StackedSearch);
}
break;
}
vehicleRoutingOptimizer = new ParallelMultistart(multistartParameters);
toRenderBackground = false;
foreach (ISolution solution in vehicleRoutingOptimizer.Minimize(startSolution))
{
if (worker.CancellationPending)
{
vehicleRoutingOptimizer.Stop();
e.Cancel = true;
}
if (e.Cancel)
{
solution.IsFinal = false;
}
worker.ReportProgress(0);
}
}
private void bwFloorplan_DoWork(object sender, DoWorkEventArgs e)
{
BackgroundWorker worker = (BackgroundWorker)sender;
algorithmStatus.Text = "Press ESC to cancel";
FloorplanProblem problem = new FloorplanProblem(floorplanRectangles);
FloorplanSolution startSolution = new FloorplanSolution(problem);
Swap swap = new Swap(problem.Dimension, 10);
Shift shift = new Shift(problem.Dimension, 1);
EmptyLeafMove eLeaf = new EmptyLeafMove(problem.Dimension, 5);
FullLeafMove fLeaf = new FullLeafMove(problem.Dimension, 5);
FullNodeMove fNode = new FullNodeMove(problem.Dimension, 5);
MultistartParameters multistartParameters = (MultistartParameters)multistartOptions.Clone();
LocalDescentParameters ldParameters = new LocalDescentParameters()
{
Name = "VLSI LD",
Seed = seed,
DetailedOutput = true,
Operators = new List <Operator> {
swap, fLeaf
}
};
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters()
{
Name = "VLSI SA",
InitProbability = 0.5,
TemperatureCooling = 0.96,
MinCostDeviation = 0,
Seed = seed,
DetailedOutput = true,
Operators = new List <Operator> {
swap, fNode
}
};
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 = 0.005;
saParameters.TemperatureCooling = 0.95;
multistartParameters.Parameters = ssParameters;
multistartParameters.OptimizationAlgorithm = typeof(StackedSearch);
}
break;
case 3:
{
saParameters.InitProbability = 0.005;
saParameters.TemperatureCooling = 0.95;
multistartParameters.InstancesNumber = 3;
multistartParameters.Parameters = ssParameters;
multistartParameters.OptimizationAlgorithm = typeof(StackedSearch);
}
break;
}
floorplanOptimizer = new ParallelMultistart(multistartParameters);
toRenderBackground = false;
foreach (ISolution solution in floorplanOptimizer.Minimize(startSolution))
{
if (worker.CancellationPending)
{
floorplanOptimizer.Stop();
e.Cancel = true;
}
worker.ReportProgress(0);
}
}
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();
}
static void Main(string[] args)
{
//VehicleRoutingProblem vrProblem = new VehicleRoutingProblem(4, 2);
//VehicleRoutingSolution vrSolution = new VehicleRoutingSolution(vrProblem);
//Console.WriteLine(vrSolution.ToString());
//Console.WriteLine(vrSolution.CostValue);
//Console.ReadLine();
//return;
//FloorplanProblem problem = new FloorplanProblem(100);
//FloorplanProblem problem = FloorplanProblem.Load("500.vlsi");
//FloorplanSolution solution = new FloorplanSolution(problem);
//Swap swap = new Swap(problem.Dimension, 10);
//Shift shift = new Shift(problem.Dimension, 1);
//EmptyLeafMove eLeaf = new EmptyLeafMove(problem.Dimension, 5);
//FullLeafMove fLeaf = new FullLeafMove(problem.Dimension, 5);
//FullNodeMove fnode = new FullNodeMove(problem.Dimension, 5);
//List<Operator> operations = new List<Operator> { swap, fLeaf };
//TspProblem problem = new TspProblem(200);
//TspSolution solution = new TspSolution(problem);
VehicleRoutingProblem problem = new VehicleRoutingProblem(225, 10);
VehicleRoutingSolution solution = new VehicleRoutingSolution(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()
{
Name = "P",
InstancesNumber = 5,
RandomizeStart = false,
DetailedOutput = true,
OutputFrequency = 100,
};
LocalDescentParameters ldParameters = new LocalDescentParameters()
{
Name = "LD",
DetailedOutput = true,
Seed = 0,
Operators = operations,
IsSteepestDescent = false
};
SimulatedAnnealingParameters saParameters = new SimulatedAnnealingParameters()
{
Name = "SA",
InitProbability = 0.5,
TemperatureCooling = 0.98,
MinCostDeviation = 0,
UseWeightedNeighborhood = false,
DetailedOutput = false,
Seed = 0,
Operators = operations,
};
MultistartParameters pldParameters = (MultistartParameters)multistartOptions.Clone();
pldParameters.OptimizationAlgorithm = typeof(LocalDescent);
pldParameters.Parameters = ldParameters;
MultistartParameters psaParameters = (MultistartParameters)multistartOptions.Clone();
psaParameters.OptimizationAlgorithm = typeof(SimulatedAnnealing);
psaParameters.Parameters = saParameters;
StackedParameters ssParameters = new StackedParameters()
{
Name = "B",
DetailedOutput = true,
OptimizationAlgorithms = new Type[] { typeof(LocalDescent), typeof(SimulatedAnnealing), typeof(LocalDescent) },
Parameters = new OptimizationParameters[] { ldParameters, saParameters, ldParameters }
};
StackedParameters sspParameters = new StackedParameters()
{
Name = "B",
DetailedOutput = false,
OptimizationAlgorithms = new Type[] { typeof(LocalDescent), typeof(ParallelMultistart), typeof(LocalDescent) },
Parameters = new OptimizationParameters[] { ldParameters, psaParameters, ldParameters }
};
LocalDescent ld = new LocalDescent(ldParameters);
SimulatedAnnealing sa = new SimulatedAnnealing(saParameters);
ParallelMultistart pld = new ParallelMultistart(pldParameters);
ParallelMultistart psa = new ParallelMultistart(psaParameters);
StackedSearch ss = new StackedSearch(ssParameters);
StackedSearch ssp = new StackedSearch(sspParameters);
MultistartParameters pssParameters = (MultistartParameters)multistartOptions.Clone();
pssParameters.DetailedOutput = false;
pssParameters.RandomizeStart = true;
pssParameters.OptimizationAlgorithm = typeof(StackedSearch);
pssParameters.Parameters = ssParameters;
ParallelMultistart pss = new ParallelMultistart(pssParameters);
IOptimizationAlgorithm optimizer = sa;
ISolution bestSolution = solution;
foreach (ISolution s in optimizer.Minimize(solution.Shuffle(0)))
{
//if (s.IsCurrentBest)
Console.WriteLine("\t{0}, {1:f}s, {2}, {3}, {4}, {5}, {6}", s.CostValue, s.TimeInSeconds, s.IterationNumber, s.IsCurrentBest, s.IsFinal, bestSolution.CostValue - s.CostValue, s.InstanceTag);
bestSolution = s;
}
Console.WriteLine(bestSolution.TimeInSeconds + "s");
Console.WriteLine(bestSolution.IterationNumber + " iterations");
//var groups = optimizer.SearchHistory.GroupBy(s => s.OperatorTag).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");
foreach (var b in DrawSolution(bestSolution, optimizer))
{
b?.Save("solution" + DateTime.Now.Millisecond + ".jpg");
}
Console.ReadLine();
}
