private GeneticAlgorithm CreateGaGroupingProblemSample()
{
GeneticAlgorithm ga = new GeneticAlgorithm();
#region Problem Configuration
var problem = new SingleObjectiveProgrammableProblem()
{
ProblemScript = { Code = ProblemCode }
};
problem.ProblemScript.Compile();
#endregion
#region Algorithm Configuration
ga.Name = "Genetic Algorithm - Graph Coloring";
ga.Description = "A genetic algorithm which solves a graph coloring problem using the linear linkage encoding.";
ga.Problem = problem;
SamplesUtils.ConfigureGeneticAlgorithmParameters <TournamentSelector, MultiLinearLinkageCrossover, MultiLinearLinkageManipulator>(
ga, 100, 1, 1000, 0.05, 2);
#endregion
return(ga);
}
private GeneticAlgorithm CreateGaGroupingProblemSample() {
GeneticAlgorithm ga = new GeneticAlgorithm();
#region Problem Configuration
var problem = new SingleObjectiveProgrammableProblem() {
ProblemScript = { Code = ProblemCode }
};
problem.ProblemScript.Compile();
#endregion
#region Algorithm Configuration
ga.Name = "Genetic Algorithm - Grouping Problem";
ga.Description = "A genetic algorithm which solves a grouping problem using the linear linkage encoding.";
ga.Problem = problem;
SamplesUtils.ConfigureGeneticAlgorithmParameters<TournamentSelector, MultiLinearLinkageCrossover, MultiLinearLinkageManipulator>(
ga, 100, 1, 1000, 0.05, 2);
#endregion
return ga;
}
