public void Solve()
{
SudokuBoard sudokuBoard = Transform(Sudoku);
IChromosome chromosome = new SudokuPermutationsChromosome(sudokuBoard);
var fitness = new SudokuFitness(sudokuBoard);
var selection = new EliteSelection();
var crossover = new UniformCrossover();
var mutation = new UniformMutation();
var population = new Population(5000, 5000, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation)
{
Termination = new OrTermination(new ITermination[]
{
new FitnessThresholdTermination(0),
new GenerationNumberTermination(100)
})
};
ga.Start();
var bestIndividual = ((ISudokuChromosome)ga.Population.BestChromosome);
var solutions = bestIndividual.GetSudokus();
Sudoku = Transform(solutions[0]);
}
public void Evolve_SimpleSudokuPermutationsChromosome_Solved()
{
var sudoku = SudokuTestHelper.CreateBoard();
IChromosome chromosome = new SudokuPermutationsChromosome(sudoku);
var fitness = SudokuTestHelper.Eval(chromosome, sudoku, 1000, 0, 50);
Assert.AreEqual(fitness, 0);
}
public void Evolve_RandomPermutationsChromosome_EasySudoku_Solved()
{
var sudoku = SudokuTestHelper.CreateBoard(SudokuTestDifficulty.Easy);
IChromosome chromosome = new SudokuPermutationsChromosome(sudoku);
var fitness = SudokuTestHelper.Eval(chromosome, sudoku, 1000, 0, 40);
Assert.AreEqual(0, fitness);
}
public void Constructor_NoArgs_Length9()
{
var target = new SudokuPermutationsChromosome();
Assert.AreEqual(9, target.Length);
var genes = target.GetGenes();
Assert.AreEqual(9, genes.Length);
}