GiveAGap 1.0.3

Headings Install the package and then add at least this line of code below to run once the algorithm Code Block var mutationProb = 0.1f; var crossOverProb = 0.8f; var dimVincoli = 1000; var dimVars = 15; var trPerc = 0.5; var vdPerc = 0.25; var myTest = new SynthTest(dimVincoli, dimVars, trPerc, vdPerc, 1, 1); // or Create another test expanding SynthTest.cs GeneticAlgorithmSETUP setup = new GeneticAlgorithmSETUP(myTest, dimVincoli, dimVars, trPerc, vdPerc, 1, crossOverProb, mutationProb); setup.minFit = 0.45; setup.forcedINOUT = Vector<double>.Build.Dense(setup.dimVars); // modify your ForcedInOutClass var forcedINOUT = setup.forcedINOUT; var result = setup.Start(0.8,30,true); // Termination Conditions (minFit,minGen,and) Console.WriteLine("SELECTED: " + result.Item1); Console.WriteLine("In " + result.Item2 + " generations"); Console.WriteLine("In " + result.Item3 + " seconds"); Console.WriteLine("Fitness on TS " + result.Item4); Console.WriteLine("Fitness on TR VD " + result.Item5); Console.WriteLine("*****************"); Explaination Basically you need to choose mutation and crossover probability, then setup the algorithm giving him the size of the input Matrix, and then calling setup.Start() the algorithm starts and when execution finishes you get a tuple with all element you need for the analysis