public Fitness ( double parameters, double fitnessLimit ) : double | ||
parameters | double | Parameters to use for the Optimizer. |
fitnessLimit | double | Preemptive Fitness Limit |
return | double |
static void Main(string[] args) { // Create and initialize PRNG. Globals.Random = new RandomOps.MersenneTwister(); // Assign run-condition to problem. Problem.RunCondition = RunCondition; // Wrap the optimizer in a logger of result-statistics. Statistics Statistics = new Statistics(Optimizer); // Wrap it again in a repeater. Repeat repeat = new RepeatSum(Statistics, NumRuns); // Output optimization settings. Console.WriteLine("Problem: {0}", Problem.Name); Console.WriteLine("Optimizer: {0}", Optimizer.Name); Console.WriteLine("Using following parameters:"); Tools.PrintParameters(Optimizer, Optimizer.DefaultParameters); Console.WriteLine("Number of runs: {0}", NumRuns); Console.WriteLine("Dimensionality: {0}", Dim); Console.WriteLine("Dim-factor: {0}", DimFactor); Console.WriteLine(); // Start-time. DateTime t1 = DateTime.Now; // Perform optimizations. double fitness = repeat.Fitness(); // End-time. DateTime t2 = DateTime.Now; // Compute result-statistics. Statistics.Compute(); // Output best results, as well as result-statistics. Console.WriteLine("Best parameters found:"); Tools.PrintParameters(Problem, Statistics.BestParameters); Console.WriteLine("With fitness: {0}", Tools.FormatNumber(Statistics.FitnessMin)); Console.WriteLine("Time usage: {0}", t2 - t1); Console.WriteLine("Mean number of iterations: {0}", Statistics.IterationsMean); Console.WriteLine(); Console.WriteLine("x\ty\tComputedY"); Console.WriteLine("--------------------"); // Output fitted curve. for (int i=0; i<X.Length; i++) { double x = X[i]; double y = Y[i]; double computedY = Problem.ComputeY(Statistics.BestParameters, x); Console.WriteLine("{0}\t{1}\t{2}", x, y, computedY); } }
/// <summary> /// Optimize the given problem and output result-statistics. /// </summary> static void Optimize(Problem problem) { // Create a fitness trace for tracing the progress of optimization, mean. int NumMeanIntervals = 3000; FitnessTrace fitnessTraceMean = new FitnessTraceMean(NumIterations, NumMeanIntervals); // Create a fitness trace for tracing the progress of optimization, quartiles. // Note that fitnessTraceMean is chained to this object by passing it to the // constructor, this causes both fitness traces to be used. int NumQuartileIntervals = 10; FitnessTrace fitnessTraceQuartiles = new FitnessTraceQuartiles(NumRuns, NumIterations, NumQuartileIntervals, fitnessTraceMean); // Assign the problem etc. to the optimizer. Optimizer.Problem = problem; Optimizer.RunCondition = RunCondition; Optimizer.FitnessTrace = fitnessTraceQuartiles; // Wrap the optimizer in a logger of result-statistics. Statistics Statistics = new Statistics(Optimizer); // Wrap it again in a repeater. Repeat Repeat = new RepeatSum(Statistics, NumRuns); // Perform the optimization runs. double fitness = Repeat.Fitness(Parameters); // Compute result-statistics. Statistics.Compute(); // Output result-statistics. Console.WriteLine("{0} & {1} & {2} & {3} & {4} & {5} & {6} & {7} \\\\", problem.Name, Tools.FormatNumber(Statistics.FitnessMean), Tools.FormatNumber(Statistics.FitnessStdDev), Tools.FormatNumber(Statistics.FitnessQuartiles.Min), Tools.FormatNumber(Statistics.FitnessQuartiles.Q1), Tools.FormatNumber(Statistics.FitnessQuartiles.Median), Tools.FormatNumber(Statistics.FitnessQuartiles.Q3), Tools.FormatNumber(Statistics.FitnessQuartiles.Max)); // Output fitness trace, mean. string traceFilenameMean = Optimizer.Name + "-FitnessTraceMean-" + problem.Name + ".txt"; fitnessTraceMean.WriteToFile(traceFilenameMean); // Output fitness trace, quartiles. string traceFilenameQuartiles = Optimizer.Name + "-FitnessTraceQuartiles-" + problem.Name + ".txt"; fitnessTraceQuartiles.WriteToFile(traceFilenameQuartiles); }