public static void RunIntroOptimization()
{
var solutionSpace = new IntervalBranch(0, 3.2);
var bb = new SIDBranchAndBound <double>(solutionSpace, FitnessFunctions.ExampleFunction, GuidingParameter.OneOverNthQuantile);
var result = bb.BranchAndBound(200, 8, 0.99, false, false);
Program.logger.WriteLine("Intro Optimization Results:");
for (int i = 0; i < result.Length; i++)
{
Program.logger.WriteLine($"{i}: {result[i].ToString()}");
}
}
public static void RunEggholderOptimization()
{
var solutionSpace = new RectangleBranch(-512, 512, -512, 512); // Constraints
const int sampleSize = 200;
const double confidenceLevel = 0.99;
const int numSteps = 6;
var bb = new SIDBranchAndBound <Tuple <double, double> >(solutionSpace, x => FitnessFunctions.EggHolder(x.Item1, x.Item2), GuidingParameter.OneOverNthQuantile);
var result = bb.BranchAndBound(sampleSize, numSteps, confidenceLevel, false, false);
Program.logger.WriteLine($"Eggholder Size {sampleSize} Confidence {confidenceLevel} Optimization Results:");
for (int i = 0; i < result.Length; i++)
{
Program.logger.WriteLine($"{i}: {result[i].ToString()}");
}
}
public static void RunWickedCombOptimization()
{
var solutionSpace = new IntervalBranch(-0.15, 0.15); // Constraints
const double difficulty = 5;
const double xSquaredCoefficient = 10;
const int sampleSize = 200;
const double confidenceLevel = 0.99;
const int numSteps = 15;
var bb = new SIDBranchAndBound <double>(solutionSpace, x => FitnessFunctions.WickedComb(x, difficulty, xSquaredCoefficient), GuidingParameter.OneOverNthQuantile);
var result = bb.BranchAndBound(sampleSize, numSteps, confidenceLevel, false, false);
Program.logger.WriteLine($"Wicked Comb (x, {difficulty}, {xSquaredCoefficient}) Size {sampleSize} Confidence {confidenceLevel} Optimization Results:");
for (int i = 0; i < result.Length; i++)
{
Program.logger.WriteLine($"{i}: {result[i].ToString()}");
}
}
public static void RunEMSOptimization()
{
EMSOptimizationOverhaul.Program.ImportData(3); // Use both years of data
//var solutionSpace = new OneDimInterval(start: 2, end: 4, SampleSize: 100, rand: rand);
//var solutionSpace = new TwoDimInterval(StartX: -10, EndX: 10, StartY: -10, EndY: 10, SampleSize: 30, rand: rand);
var solutionSpace = new PartialEMSPlanBranch(
//CurrentPlanFullAmbs: new int[] { 2, 0, 1, 0, 0, 0, 1, 1, 0, 2 }, // CK, Crum, Dun, EL, FtG, KenSub, Lav, Pri, SpV, Wayne
FullAmbs: new int[Station.List.Count],
PartAmbs: new int[Station.List.Count],
TargetAmbulanceCount: 10,
rand: Program.rand);
var Problem = new SIDBranchAndBound <Tuple <int[], int[]> >(solutionSpace, FitnessFunctions.EMSPlanFitness, GuidingParameter.OneOverNthQuantile);
Logging.Log("Problem Initialized");
Branch[] branchSet = Problem.BranchAndBound(sampleSize: 5000, iterations: 9, confidenceLevel: 0.99, cullDuplicates: true, multiThread: true);
// Print the set of branches produced by the B&B routine
foreach (Branch branch in branchSet)
{
Program.logger.WriteLine("");
var plan = (PartialEMSPlanBranch)branch;
Program.logger.WriteLine("Region: ");
for (int i = 0; i < Station.List.Count; i++)
{
Program.logger.Write($"Station: {Station.List[i].Name} Full: {plan.FullAmbs[i]} Part: {plan.PartAmbs[i]}");
}
//Console.WriteLine($"Best score: {branch.BestObservation}");
//bestObserved = Math.Min(bestObserved, branch.BestObservation);
}
// Do an exhaustive search of the reduced search space to find the set of optima
//double bestObserved = double.PositiveInfinity;
// ...
Program.logger.WriteLine("");
Program.logger.WriteLine($"Best observed in all regions :{Problem.BestElementObserved} fitness: {Problem.BestFitnessObserved}");
}
