public static List <int> GetCandidates(UniqueModelCase model, float targetFunEvaluation)
{
//Lista de los casos candidatos a remover (un índice del caso).
List <int> candidates = new List <int>();
var percentajes = model.GetPercentajes();
var obtained3 = percentajes.Item1;
var obtained4 = percentajes.Item2;
// Recorro la lista total de casos de prueba.
foreach (var caseToRemove in model.Results.Keys)
{
// Verifio si mejora la evaluación de la función objetivo.
percentajes = model.GetPercentajeIfRemove(caseToRemove);
float ifRemove3 = percentajes.Item1;
float ifRemove4 = percentajes.Item2;
//Console.WriteLine($"Diference if remove case {k} in 3: {ifRemove3}");
//Console.WriteLine($"Diference if remove case {k} in 4: {ifRemove4}");
//var newObtained3 = obtained3 + ifRemove3;
//var newObtained4 = obtained4 + ifRemove4;
float newTargetFunEvaluation = Sett.TargetFunc(ifRemove3, ifRemove4);
//Console.WriteLine($"New total diference = {newTargetFunEvaluation}");
//Console.WriteLine();
// Si la mejora entonces es candidato
if (newTargetFunEvaluation < targetFunEvaluation)
{
candidates.Add(caseToRemove);
}
}
return(candidates);
}
private static IEnumerable <UniqueModelCase> SplitModel(UniqueModelCase model)
{
int n = 5;
UniqueModelCase[] modelArray = new UniqueModelCase[n];
for (int i = 0; i < n; i++)
{
modelArray[i] = new UniqueModelCase(SolutionComparer.EqPol);
}
foreach (var k in model.Results.Keys)
{
modelArray[k % n].AddCase(k, model.Results[k]);
}
return(modelArray);
}
public override UniqueModelCase Run(UniqueModelCase model)
{
var result = new UniqueModelCase(model.Results, model._eq);
Helper.CheckCases(result.Results.Values);
// Obtengo la lista de canditados a eliminar de los casos de prueba.
// Un caso de prueba es candidato si mejora la evaluacíón de la función objetivo.
var percentajes = result.GetPercentajes();
float funcEval = Sett.TargetFunc(percentajes.Item1, percentajes.Item2);
List <int> candidates = GetCandidates(result, funcEval);
// Mientras pueda mejorar la evalución de la función (> 0) y tenga candidatos a eliminar.
int n = 500;
while (candidates.Count > 0 && n-- > 0)
{
// Selecciono un candidato random a eliminar.
var caseToDelete = candidates[Sett.Rnd.Next(candidates.Count)];
result.RemoveCase(caseToDelete);
// Elimino el caso y actualizo la evaluación de la función objetivo.
percentajes = result.GetPercentajes();
funcEval = Sett.TargetFunc(percentajes.Item1, percentajes.Item2);
// Obtengo la nueva lista de candidatos.
candidates = GetCandidates(result, funcEval);
//Console.WriteLine($"Count candidates: {candidates.Count}");
}
percentajes = result.GetPercentajes();
funcEval = Sett.TargetFunc(percentajes.Item1, percentajes.Item2);
Console.WriteLine($"Final diference: {funcEval}");
Helper.CheckCases(result.Results.Values);
return(result);
}
public override UniqueModelCase Run(UniqueModelCase model)
{
var modelSplited = SplitModel(model);
// Solo para poderle aplicar lambda.
var solutionsList = new List <UniqueModelCase>(modelSplited);
var percentajes = solutionsList.Select(p => p.GetPercentajes());
var evals = percentajes.Select(p => Sett.TargetFunc(p)).ToArray();
string fo = Directory.GetCurrentDirectory() + @"\" + "fo " + Sett.i + ".txt";
string calls = Directory.GetCurrentDirectory() + @"\" + "calls " + Sett.i + ".txt";
using (StreamWriter file = new StreamWriter(fo, true))
{
file.Write(evals.Min() + ", ");
}
using (StreamWriter file = new StreamWriter(calls, true))
{
file.Write(Sett.calls - Sett.callsAux + ", ");
Sett.callsAux = Sett.calls;
}
int n = 500;
while (n-- > 0)
{
percentajes = solutionsList.Select(k => k.GetPercentajes());
evals = percentajes.Select(k => Sett.TargetFunc(k)).ToArray();
// Selección de los individuos.
var couple1Indexs = MergeAndFind.Find2Bests(evals);
var couple2Indexs = MergeAndFind.Find2Random(evals);
var c1x = solutionsList[couple1Indexs.Item1];
var c1y = solutionsList[couple1Indexs.Item2];
var c2x = solutionsList[couple2Indexs.Item1];
var c2y = solutionsList[couple2Indexs.Item2];
// Aplicación de operadores.
var resultc1A = MergeAndFind.Merge1(c1x.Results, c1y.Results);
var resultc1B = MergeAndFind.Merge2(c1x.Results, c1y.Results);
var resultc1C = MergeAndFind.Merge3(c1x.Results, c1y.Results);
var resultc1D = MergeAndFind.Merge4(c1x.Results, c1y.Results, (int)((float)c1x.Results.Count * 80 / 100), (int)((float)c2y.Results.Count * 20 / 100));
var resultc2A = MergeAndFind.Merge1(c2x.Results, c2y.Results);
var resultc2B = MergeAndFind.Merge2(c2x.Results, c2y.Results);
var resultc2C = MergeAndFind.Merge3(c2x.Results, c2y.Results);
var resultc2D = MergeAndFind.Merge4(c2x.Results, c2y.Results, (int)((float)c2x.Results.Count * 80 / 100), (int)((float)c2y.Results.Count * 20 / 100));
var currentComparer = model._eq;
var c1 = new UniqueModelCase(resultc1A, currentComparer);
var c2 = new UniqueModelCase(resultc1B, currentComparer);
var c3 = new UniqueModelCase(resultc1C, currentComparer);
var c4 = new UniqueModelCase(resultc1D, currentComparer);
var c5 = new UniqueModelCase(resultc2A, currentComparer);
var c6 = new UniqueModelCase(resultc2B, currentComparer);
var c7 = new UniqueModelCase(resultc2C, currentComparer);
var c8 = new UniqueModelCase(resultc2D, currentComparer);
var newSolutions = new UniqueModelCase[] { c1, c2, c3, c4, c5, c6, c7, c8 };
solutionsList.AddRange(newSolutions);
var newPercentajes = solutionsList.Select(k => k.GetPercentajes());
var newEvals = newPercentajes.Select(k => Sett.TargetFunc(k)).ToList();
for (int i = 0; i < 4; i++)
{
int index = Filter(newEvals);
solutionsList.RemoveAt(index);
newEvals.RemoveAt(index);
}
using (StreamWriter file = new StreamWriter(fo, true))
{
file.Write(evals.Min() + ", ");
}
using (StreamWriter file = new StreamWriter(calls, true))
{
file.Write(Sett.calls - Sett.callsAux + ", ");
Sett.callsAux = Sett.calls;
}
}
var min = evals.Min();
Console.WriteLine($"Menor evaluación {min}");
return(model = solutionsList.First(p => Sett.TargetFunc(p.GetPercentajes()) == min));
}
public abstract UniqueModelCase Run(UniqueModelCase model);
static void Main(string[] args)
{
//Helper.WriteFormatedCases();
//// Generador de casos de prueba aleatorios.
//var generator = new CaseGenerator();
////Método que me genera n casos de prueba.
////if (generate)
////{
////var cases = generator.GenerateCases(Sett.CasesToGenerate);
////SaveData(cases, "Cases.txt");
///
while (Sett.i++ < 100)
{
Sett.calls = 0;
Sett.callsAux = 0;
var cases = ReadPolData();
//var cases = ReadAnaData();
////}
List <object> sols3 = new List <object>();
List <object> sols4 = new List <object>();
List <object> sols5 = new List <object>();
List <object>[] sols = new List <object>[] { sols3, sols4, sols5 };
RunPolCases(cases, sols, Sett.MethodPolNames);
//RunAnaCases(cases, sols, Sett.MethodAnaNames);
//Console.WriteLine("---");
//UniqueModelCase model = new UniqueModelCase(SolutionComparer.EqAna);
UniqueModelCase model = new UniqueModelCase(SolutionComparer.EqPol);
// Separo en casos de acierto y en casos de error para cada implementación.
model.SplitCases(sols3, sols5, 1);
model.SplitCases(sols4, sols5, 2);
// Calculo el % de acierto.
var obtained = model.GetPercentajes();
var obtained3 = obtained.Item1;
var obtained4 = obtained.Item2;
Console.WriteLine($"Model 3: {obtained3}%");
Console.WriteLine($"Model 4: {obtained4}%");
//Console.WriteLine($"Model 5: 100%");
// Evaluación de la función objetivo a minimizar.
float targetFunEvaluation = Sett.TargetFunc(obtained3, obtained4);
Console.WriteLine($"Total diference: {targetFunEvaluation}");
Console.WriteLine(model.Results.Count);
//Sett.calls = 0;
//var grasp = new GRASP();
//model = grasp.Run(model);
var ga = new GeneticAlgorithm();
model = ga.Run(model);
}
//obtained = model.GetPercentajes();
//obtained3 = obtained.Item1;
//obtained4 = obtained.Item2;
//Console.WriteLine($"Model 3: {obtained3}%");
//Console.WriteLine($"Model 4: {obtained4}%");
//targetFunEvaluation = Sett.TargetFunc(obtained3, obtained4);
//Console.WriteLine(model.Results.Count);
//Helper.CheckCases(model.Results.Values);
//var finalCases = Helper.GetFinalCases(cases, model.Results.Keys);
//Helper.WriteFinalCases(finalCases);
//Console.WriteLine(string.Join("\n", finalCases));
//int i = 0;
//string p = Directory.GetCurrentDirectory() + @"\" + "3.txt";
//using (StreamWriter file = new StreamWriter(p, false))
//{
// foreach (var k in model.Results.Keys)
// {
// var s = "";
// if (k < 10)
// s = "00";
// else if (k < 100)
// s = "0";
// file.Write(s + k + " ");
// i++;
// if(i == 20)
// {
// i = 0;
// file.WriteLine();
// }
// }
//}
}
