protected override IEvaluation <bool>[] GenerateProblems()
{
int[] max3Satblocks = { 5, 10, 20, 30, 40, 50 };
int[] isgGenes = { 25, 49, 100, 484 };
int[] nkLandscapeGenes = { 10, 50, 100 };
int[] standardDeceptiveBlocks = { 10, 50, 100 };
int nProblems = max3Satblocks.Length + //Max3Sat problem
isgGenes.Length + //Ising Sping Glass
nkLandscapeGenes.Length + //NK fitness landscapes
standardDeceptiveBlocks.Length; //Standard Deceptive problem with length 3
int iterator = 0;
IEvaluation <bool>[] problems = new IEvaluation <bool> [nProblems];
//Max3Sat problem
foreach (var genes in max3Satblocks)
{
problems[iterator] = new CBinaryMax3SatEvaluation(genes);
iterator++;
}
//Ising Sping Glass
foreach (var genes in isgGenes)
{
problems[iterator] = new CBinaryIsingSpinGlassEvaluation(genes);
iterator++;
}
//NK fitness landscapes
foreach (var genes in nkLandscapeGenes)
{
problems[iterator] = new CBinaryNKLandscapesEvaluation(genes);
iterator++;
}
//Standard Deceptive problem with length 3
foreach (var functions in standardDeceptiveBlocks)
{
problems[iterator] = new CBinaryStandardDeceptiveConcatenationEvaluation(3, functions);
iterator++;
}
return(problems);
}
private static Experiment <bool> PrepareExperiment6(int evaluationType, int algorithm, int selectionMethod, int crossoverMethod, double crossoverProb, double mutationProb, int populationSize, int?seed = null)
{
IEvaluation <bool> evaluation;
Dictionary <string, string> info = new Dictionary <string, string>();
switch (evaluationType)
{
case 0:
evaluation = new CBinaryMax3SatEvaluation(100);
info["problem"] = "Max3Sat";
info["variables"] = "100";
break;
case 1:
evaluation = new CBinaryIsingSpinGlassEvaluation(100);
info["problem"] = "ISG";
info["variables"] = "100";
break;
case 2:
evaluation = new CBinaryNKLandscapesEvaluation(100);
info["problem"] = "NKLandscapes";
info["variables"] = "100";
break;
case 3:
evaluation = new CBinaryStandardDeceptiveConcatenationEvaluation(3, 10);
info["problem"] = "Deceptive";
info["variables"] = "10";
break;
case 4:
evaluation = new CBinaryStandardDeceptiveConcatenationEvaluation(3, 50);
info["problem"] = "Deceptive";
info["variables"] = "50";
break;
case 5:
evaluation = new CBinaryStandardDeceptiveConcatenationEvaluation(3, 100);
info["problem"] = "Deceptive";
info["variables"] = "100";
break;
default:
throw new ArgumentOutOfRangeException();
}
RunningTimeStopCondition stopCondition = new RunningTimeStopCondition(evaluation.dMaxValue, 30);
BinaryRandomGenerator generator = new BinaryRandomGenerator(evaluation.pcConstraint, seed);
ASelection selection;
switch (selectionMethod)
{
case 0:
selection = new RouletteWheelSelection(seed);
info["selection_method"] = "roulette";
break;
case 1:
selection = new TournamentSelection(2, seed);
info["selection_method"] = "tournament";
break;
default:
throw new ArgumentOutOfRangeException();
}
ACrossover crossover;
info["crossover_prob"] = crossoverProb.ToString();
switch (crossoverMethod)
{
case 0:
crossover = new OnePointCrossover(crossoverProb, seed);
info["crossover_method"] = "OnePoint";
break;
case 1:
crossover = new UniformCrossover(crossoverProb, seed);
info["crossover_method"] = "uniform";
break;
default:
throw new ArgumentOutOfRangeException();
}
mutationProb = mutationProb / evaluation.iSize;
info["mutation_prob"] = mutationProb.ToString();
BinaryBitFlipMutation mutation = new BinaryBitFlipMutation(mutationProb, evaluation, seed);
info["population"] = populationSize.ToString();
GeneticAlgorithm <bool> ga;
switch (algorithm)
{
case 0:
ga = new GeneticAlgorithm <bool>(evaluation, stopCondition, generator, selection, crossover, mutation, populationSize);
info["algorithm"] = "GA";
break;
case 1:
ga = new ResettingGA <bool>(evaluation, stopCondition, generator, selection, crossover, mutation, populationSize, 10, seed);
info["algorithm"] = "resetting";
break;
default:
throw new ArgumentOutOfRangeException();
}
Experiment <bool> experiment = new Experiment <bool>(ga, info, ExperimentFinished);
return(experiment);
}
protected override IEvaluation <bool>[] GenerateProblems()
{
int[] genes = { 5, 10, 20, 30, 40, 50 };
int[] standardBlocks = { 1, 2, 4, 6, 8, 10 };
int[] bimodalBlocks = { 1, 2, 3, 4, 5 };
int[] isgGenes = { 25, 49, 100, 484 };
int[] nkLandscapeGenes = { 10, 50, 100, 200 };
int nProblems = genes.Length + //OneMax
standardBlocks.Length + //Order-5 deceptive concatenation
bimodalBlocks.Length + //Bimodal-10 deceptive concatenation
isgGenes.Length + //Ising Sping Glass
nkLandscapeGenes.Length; //NK fitness landscapes
//int[] genes = { 5 };
//int[] standardBlocks = { 1 };
//int[] bimodalBlocks = { 1 };
//int[] isgGenes = { 25 };
//int[] nkLandscapeGenes = { 10 };
//int nProblems = genes.Length + //OneMax
// standardBlocks.Length + //Order-5 deceptive concatenation
// bimodalBlocks.Length + //Bimodal-10 deceptive concatenation
// isgGenes.Length + //Ising Sping Glass
// nkLandscapeGenes.Length; //NK fitness landscapes
int iterator = 0;
IEvaluation <bool>[] problems = new IEvaluation <bool> [nProblems];
//OneMax
foreach (int gene in genes)
{
problems[iterator] = new CBinaryOneMaxEvaluation(gene);
iterator++;
}
//Order-5 deceptive concatenation
foreach (int block in standardBlocks)
{
problems[iterator] = new CBinaryStandardDeceptiveConcatenationEvaluation(5, block);
iterator++;
}
//Bimodal-10 deceptive concatenation
foreach (int block in bimodalBlocks)
{
problems[iterator] = new CBinaryBimodalDeceptiveConcatenationEvaluation(10, block);
iterator++;
}
//Ising Sping Glass
foreach (int gene in isgGenes)
{
problems[iterator] = new CBinaryIsingSpinGlassEvaluation(gene);
iterator++;
}
//NK fitness landscapes
foreach (int gene in nkLandscapeGenes)
{
problems[iterator] = new CBinaryNKLandscapesEvaluation(gene);
iterator++;
}
return(problems);
}