public Gene(Gene mother, Gene father, bool mutate)
{
// Inherit chromosomes from "parents".
chromosomes = new Chromosome[MAX_CHROMOSOMES];
chromosomes[0] = mother.chromosomes[0];
chromosomes[1] = mother.chromosomes[1];
chromosomes[2] = Genetic.Random.NextBool() ? mother.chromosomes[2] : father.chromosomes[2];
chromosomes[3] = father.chromosomes[3];
chromosomes[4] = father.chromosomes[4];
if (mutate)
{
int firstToMutate = Genetic.Random.Next(0, MAX_CHROMOSOMES);
int secondToMutate = Genetic.Random.Next(0, MAX_CHROMOSOMES);
chromosomes[firstToMutate] = PredefinedChromosomes[Genetic.Random.Next(0, PredefinedChromosomes.Length)];
chromosomes[secondToMutate] = PredefinedChromosomes[Genetic.Random.Next(0, PredefinedChromosomes.Length)];
}
ComputeWeight();
ComputeValue();
CheckIfIsDesirable();
}
// gera primeira população randomica, está gerando número randomico para cada vértice. Esse número randomico varia conforme o número de vértices disponíveis.
public void GenerateRandomPopulation()
{
for (int k = 0; k < this.tamanho_populacao; k++) // tamanho da população --> rever
{
Gene newInd = new Gene(this.grafo.GetNumNodes());
newInd.InitializeIndividuo();
newInd.ShuffleIndividuo();
population.Add(k, newInd);
}
}
private void GenerateNextGeneration(ref List <Gene> genes)
{
if (genes.Count == 0)
{
while (genes.Count < GenerationSize)
{
genes.Add(new Gene());
}
return;
}
List <Gene> newGenes = new List <Gene>();
for (int i = 0; i + 1 < genes.Count; i += 2)
{
ComputeNextMutation();
Gene mother = genes[i];
Gene father = genes[i + 1];
Gene siblingA = new Gene(mother, father, mutate);
Gene siblingB = new Gene(father, mother, mutate);
if (siblingA.IsDesirableGene)
{
newGenes.Add(siblingA);
}
if (siblingB.IsDesirableGene)
{
newGenes.Add(siblingB);
}
if (mutate)
{
mutate = false;
}
mutationCounter++;
}
while (newGenes.Count < GenerationSize)
{
Gene gene = new Gene();
if (gene.IsDesirableGene)
{
newGenes.Add(gene);
}
}
genes = newGenes;
}
public bool AreGenesAttempted(List <Gene> listGenes)
{
bool areAttempted = false;
int countListGenes = listGenes.Count;
if (countListGenes == 0)
{
return(true);
}
foreach (var list in _listOfListsGenesAttempted)
{
if (countListGenes != list.Count)
{
continue;
}
for (int i = 0; i < list.Count; i++)
{
Gene attemptedGene = list[i];
bool isFound = false;
foreach (var gene in listGenes)
{
if (gene.GetType() == attemptedGene.GetType())
{
isFound = true;
break;
}
}
if (!isFound)
{
break;
}
if (i == list.Count - 1)
{
areAttempted = true;
}
}
if (areAttempted)
{
break;
}
}
return(areAttempted);
}
private void CopyBestOne(Gene ind1, Gene ind2)
{
if (ind1.avaliationValue > ind2.avaliationValue)
{
Gene novoGene = new Gene(ind2.individuo.Length);
ind2.individuo.CopyTo(novoGene.individuo, 0);
novoGene.avaliationValue = ind2.avaliationValue;
populationBuff.Add(populationBuff.Count, novoGene);
}
else
{
Gene novoGene = new Gene(ind1.individuo.Length);
ind1.individuo.CopyTo(novoGene.individuo, 0);
novoGene.avaliationValue = ind1.avaliationValue;
populationBuff.Add(populationBuff.Count, novoGene);
}
}
//Avalia toda a população
public void AvaliateFunction()
{
foreach (DictionaryEntry gene in this.population)
{
((Gene)gene.Value).AvaliateGene(this.grafo);
if (isFirst == false) // seta solução arbitraria
{
Gene novaSolucao = ((Gene)gene.Value);
solution = new Gene(novaSolucao.individuo.Length);
novaSolucao.individuo.CopyTo(solution.individuo, 0);
solution.avaliationValue = novaSolucao.avaliationValue;
isFirst = true;
}
if (((Gene)gene.Value).avaliationValue < solution.avaliationValue) // guarda o melhor gene
{
Gene novaSolucao = ((Gene)gene.Value);
solution = new Gene(novaSolucao.individuo.Length);
novaSolucao.individuo.CopyTo(solution.individuo, 0);
solution.avaliationValue = novaSolucao.avaliationValue;
EhDiferente = true;
}
}
}
//http://creationwiki.org/pt/Algoritmo_gen%C3%A9tico#Order_crossover_.28OX.29
// me basiei no crossOver OX qe é o q o guilherme implementou.
private void CrossOver(Gene ind1, Gene ind2)
{
Gene son = new Gene(this.grafo.GetNumNodes());
Gene son2 = new Gene(this.grafo.GetNumNodes());
int cut = staticRandom.Next(grafo.GetNumNodes());
int cut2 = staticRandom.Next(grafo.GetNumNodes());
while (cut >= cut2) // faz com que os cortes não sejam no msm ponto
{
cut = staticRandom.Next(grafo.GetNumNodes());
cut2 = staticRandom.Next(grafo.GetNumNodes());
}
//atribui os valores de cada um dos filhos na faixa.
if (cut2 > cut)
{
int[] buff1 = new int[this.grafo.GetNumNodes()];
int[] buff2 = new int[this.grafo.GetNumNodes()];
for (int i = cut; i < cut2; i++)
{
son.individuo[i] = ind1.individuo[i];
son2.individuo[i] = ind2.individuo[i];
}
int coun = 0;
for (int k = cut2; k < this.grafo.GetNumNodes(); k++) // registra a lista auxiliar para completar o filho , depois do corte
{
buff1[coun] = ind1.individuo[k];
buff2[coun] = ind2.individuo[k];
coun++;
}
for (int k = 0; k < cut2; k++) // antes do primeiro corte
{
buff1[coun] = ind1.individuo[k];
buff2[coun] = ind2.individuo[k];
coun++;
}
//completa os filhos
int coun2 = cut2;
int coun3 = cut2;
for (int k = 0; k < buff2.Length; k++)
{
if (son.individuo.Contains(buff2[k]) == false)
{
son.individuo[coun2] = buff2[k];
coun2++;
}
if (son2.individuo.Contains(buff1[k]) == false)
{
son2.individuo[coun3] = buff1[k];
coun3++;
}
if (coun2 >= buff2.Length)
{
coun2 = 0;
}
if (coun3 >= buff2.Length)
{
coun3 = 0;
}
}
}
//adiciona elementos na população
populationBuff.Add(populationBuff.Count, son);
populationBuff.Add(populationBuff.Count, son2);
}
