}//获得当前种群的最优适应度
public void Initializer(ref GAChromosome GAChro)
{
int flag1 = 0;
int flag2 = 1;
double flag3;
while (flag2 == 1)
{
for (int i = 0; i < p; i++)
{
flag3 = m_Random.NextDouble();
if (flag3 > 0.5 && flag1 != r)
{
GAChro.Add(1);
flag1++;
}
else
{
GAChro.Add(0);
}
}
if (flag1 == r)
{
flag2 = 0;
}
else
{
GAChro.Clear();
flag1 = 0;
}
}
}//染色体初始化
}//交叉
public void Mutation(ref GAChromosome chromose)
{
int index = ((int)m_Random.Next(0, p));
int count = ((int)m_Random.Next(0, p - index));
chromose.Reverse(index, count);
}//变异
}//变异
public int[] output()
{
int[] r = new int[p];
GAChromosome GAChr = this.GetBestChromosome();
for (int i = 0; i < p; i++)
{
r[i] = GAChr[i];
}
return(r);
}
public void Initialize(Parameter Par)
{
//PopulationSizeCalculate();
PopulationSize = 100;
if (PopulationSize >= 50)
{
ApplyElitism = true;
}
for (int i = 0; i < PopulationSize; i++)//PopulationSize为染色体数
{
GAChromosome newParent = new GAChromosome(Par);
this.Initializer(ref newParent);
newParent.FitnessCalculate();
m_thisGeneration.Add(newParent);
}
TotalFitness.Clear();
RankPopulation(m_thisGeneration);
TotalFitnessRecord();
}//初始化种群
}//染色体初始化
public void Initializer1(ref GAChromosome GAChro)
{
List <int> ones = new List <int>();
ones.Clear();
while (ones.Count < p)
{
int temp = m_Random.Next(0, n);
bool flag = true;
for (int i = 0; i < ones.Count; i++)
{
if (temp == ones[i])
{
flag = false;
continue;
}
}
if (flag)
{
ones.Add(temp);
}
}
GAChro.Clear();
for (int i = 0; i < n; i++)
{
bool flag = true;
for (int j = 0; j < ones.Count; j++)
{
if (ones[j] == i)
{
GAChro.Add(1);
ones.Remove(i);
flag = false;
}
}
if (flag)
{
GAChro.Add(0);
}
}
}
public void CrossOver(GAChromosome Dad, GAChromosome Mum, ref GAChromosome child1, ref GAChromosome child2)
{
int countDad = 0, countMum = 0;
List <int> crosspoint = new List <int>();
for (int i = 0; i < p; i++)
{
if (Dad[i] == 1)
{
countDad++;
}
if (Mum[i] == 1)
{
countMum++;
}
if (countDad == countMum)
{
crosspoint.Add(i);
}
;
}
switch (Crosstype = 1)
{
//一点交叉
case 1:
{
int count = crosspoint.Count;
int j = ((int)m_Random.Next(0, count));
int index = (int)crosspoint[j];
for (int k = 0; k < p; k++)
{
if (k <= index)
{
child1.Add(Dad[k]);
child2.Add(Mum[k]);
}
else
{
child1.Add(Mum[k]);
child2.Add(Dad[k]);
}
}
break;
}
//多点交叉
case 2:
{
for (int i = 0; i < crosspoint.Count; i++)
{
if (m_Random.NextDouble() > 0.5)
{
for (int k = crosspoint[i]; k < crosspoint[i + 1]; k++)
{
child1.Add(Dad[k]);
child2.Add(Mum[k]);
}
}
else
{
for (int k = crosspoint[i]; k < crosspoint[i + 1]; k++)
{
child1.Add(Mum[k]);
child2.Add(Dad[k]);
}
}
}
break;
}
}
}//交叉
public GAChromosome GetBestChromosome()
{
GAChromosome bestChromosome = m_thisGeneration[0];
return(bestChromosome);
}//获得当前种群的最优适应度
}//对染色体按适应度降序排序
public void CreateNextGeneration(Parameter Par)
{
m_nextGeneration.Clear();
GAChromosome bestChromo = null;
if (this.ApplyElitism) //最优秀适应度最好是否直接选择加入到新一代群体
{
bestChromo = m_thisGeneration[0];
}//取出最优染色体(已排序)
for (int i = 0; i < this.PopulationSize; i += 2)
{
//Step1选择
int iDadParent = 0;
int iMumParent = 0;
if (this.Selection == SelectionType.Tournment)//竞争法
{
iDadParent = TournamentSelection();
iMumParent = TournamentSelection();
}
else if (this.Selection == SelectionType.Roullette)//轮赌法
{
iDadParent = RoulletteSelection();
iMumParent = RoulletteSelection();
}
GAChromosome Dad = (GAChromosome)m_thisGeneration[iDadParent];
GAChromosome Mum = (GAChromosome)m_thisGeneration[iMumParent];
GAChromosome child1 = new GAChromosome(Par);
GAChromosome child2 = new GAChromosome(Par);
//Step2交叉
if (m_Random.NextDouble() < this.CrossRate)
{
CrossOver(Dad, Mum, ref child1, ref child2);
}
else
{
child1 = Dad;
child2 = Mum;
}
//Step3变异
if (m_Random.NextDouble() < this.MutationRate)
{
this.Mutation(ref child1);
this.Mutation(ref child2);
}
//Step4计算适应度
child1.FitnessCalculate();
child2.FitnessCalculate();
m_nextGeneration.Add(Dad);
m_nextGeneration.Add(Mum);
m_nextGeneration.Add(child1);
m_nextGeneration.Add(child2);
}
if (null != bestChromo)
{
m_nextGeneration.Add(bestChromo); //最优的染色体插入子代群体中
}
RankPopulation(m_nextGeneration); //按照适应度对染色体排序
m_thisGeneration.Clear(); //用新一代替换当前群体
for (int j = 0; j < this.PopulationSize; j++)
{
m_thisGeneration.Add(m_nextGeneration[j]);
}
TotalFitnessRecord();
//using (System.IO.StreamWriter file = new System.IO.StreamWriter(@"C:\BestFitness_RUE.txt", true))
//{
// file.WriteLine(m_thisGeneration[0].Fitness.ToString());
//}
this.GenerationNum++;//进化代计数
}//产生下一代种群