static void Main(string[] args)
{
//真实数据集
//string[] filepath = { "../Data/RealData/S1_500.txt", "../Data/RealData/S2_500.txt", "../Data/RealData/S3_500.txt", "../Data/RealData/S4_500.txt", "../Data/RealData/S5_500.txt" };//数据集规模500
string[] filepath = { "../Data/RealData/S1_400.txt", "../Data/RealData/S2_400.txt", "../Data/RealData/S3_400.txt", "../Data/RealData/S4_400.txt", "../Data/RealData/S5_400.txt" };//数据集规模400
//string[] filepath = { "../Data/RealData/S1_300.txt", "../Data/RealData/S2_300.txt", "../Data/RealData/S3_300.txt", "../Data/RealData/S4_300.txt", "../Data/RealData/S5_300.txt" };//数据集规模300
//string[] filepath = { "../Data/RealData/S1_200.txt", "../Data/RealData/S2_200.txt", "../Data/RealData/S3_200.txt", "../Data/RealData/S4_200.txt", "../Data/RealData/S5_200.txt" };//数据集规模200
//string[] filepath = { "../Data/RealData/S1_100.txt", "../Data/RealData/S2_100.txt", "../Data/RealData/S3_100.txt", "../Data/RealData/S4_100.txt", "../Data/RealData/S5_100.txt" };//数据集规模100
//随机数据集
//string[] filepath = { "../Data/Random/S1_500.txt", "../Data/Random/S2_500.txt", "../Data/Random/S3_500.txt", "../Data/Random/S4_500.txt", "../Data/Random/S5_500.txt" };//数据集规模500
//string[] filepath = { "../Data/Random/S1_400.txt", "../Data/Random/S2_400.txt", "../Data/Random/S3_400.txt", "../Data/Random/S4_400.txt", "../Data/Random/S5_400.txt" };//数据集规模400
//string[] filepath = { "../Data/Random/S1_300.txt", "../Data/Random/S2_300.txt", "../Data/Random/S3_300.txt", "../Data/Random/S4_300.txt", "../Data/Random/S5_300.txt" };//数据集规模300
//string[] filepath = { "../Data/Random/S1_200.txt", "../Data/Random/S2_200.txt", "../Data/Random/S3_200.txt", "../Data/Random/S4_200.txt", "../Data/Random/S5_200.txt" };//数据集规模200
//string[] filepath = { "../Data/Random/S1_100.txt", "../Data/Random/S2_100.txt", "../Data/Random/S3_100.txt", "../Data/Random/S4_100.txt", "../Data/Random/S5_100.txt" };//数据集规模100
GA_Server bestserver = new GA_Server();
List <GA_Server> scrlist = new List <GA_Server>();
List <Server>[] wlist = new List <Server> [ConstNum.PARTICE_DIM];
double fit = 0, totaltime = 0;
wlist = GetData.splitedatafromfile(filepath, ConstNum.PARTICE_DIM);
Timing dobj = new Timing();
int sum = 0;
double totalfit = 0;
double RMSE = 0;
double[] ttfit = new double[101];
for (int i = 0; i < 100; i++)
{
scrlist = GA_Server.GetinitGA_server(wlist);
dobj.startTime();
bestserver = GA.GetBest(scrlist, wlist, ref fit);
dobj.StopTime();
totaltime += dobj.Result().Milliseconds;
totaltime += dobj.Result().Seconds * 1000;
totalfit += fit;
ttfit[i] = fit;
if (Math.Abs(fit - 0.5608) <= 0.0005)//QWS--500,400
{
sum++;
}
//if (Math.Abs(fit - 0.6835) <= 0.0005)//QWS-300
//{
// sum++;
//}
//if (Math.Abs(fit - 0.7802) <= 0.0005)//QWS-200
//{
// sum++;
//}
//if (Math.Abs(fit - 0.8733) <= 0.0005)//QWS-100
//{
// sum++;
//}
//if (Math.Abs(fit - 1.4482) <= 0.0005)//RWS--500
//{
// sum++;
//}
//if (Math.Abs(fit - 1.4569) <= 0.0005)//RWS--400
//{
// sum++;
//}
//if (Math.Abs(fit - 1.4742) <= 0.0005)//RWS--300
//{
// sum++;
//}
//if (Math.Abs(fit - 1.5292) <= 0.0005)//RWS--200
//{
// sum++;
//}
//if (Math.Abs(fit - 1.5711) <= 0.0005)//RWS--100
//{
// sum++;
//}
Console.WriteLine("Best fit={0}", fit);
Console.WriteLine("The Best combination is {0},{1},{2},{3},{4}", bestserver.getIndextask(0), bestserver.getIndextask(1), bestserver.getIndextask(2), bestserver.getIndextask(3), bestserver.getIndextask(4));
Console.WriteLine("The time cost is {0}ms,{1}s,********{2}", dobj.Result().Milliseconds, dobj.Result().Seconds, sum);
}
//求均方根误差
for (int i = 0; i < 100; i++)
{
RMSE += (ttfit[i] - totalfit / 100) * (ttfit[i] - totalfit / 100);
}
RMSE = RMSE / 100;
RMSE = Math.Sqrt(RMSE);
//Console.WriteLine("Average is {0},time is {1},RMSE is {2},*******{3}", totalfit/ 100, totaltime / 100,RMSE,(double)sum/100);
Console.WriteLine("Average is {0}", totalfit / 100);
Console.WriteLine("time is {0}", totaltime / 100);
Console.WriteLine("RMSE is {0}", RMSE);
Console.WriteLine("*******{0}", (double)sum / 100);
Console.ReadKey();
}
public static GA_Server GetBest(List <GA_Server> scrlist, List <Server>[] wlist, ref double fit)//scrlist表示初始种群，wlist表示子服务集
{
GA_Server globalbest = new GA_Server();
double bestfit = 100;
Random rad = new Random();
List <GA_Server> dlist = new List <GA_Server>();
for (int i = 0; i < scrlist.Count; i++)
{
dlist.Add(new GA_Server());
}
for (int t = 0; t < ConstNum.T; t++)
{
for (int i = 0; i < scrlist.Count; i++)//求每个粒子的适应度
{
scrlist[i].fitness(wlist);
}
for (int i = 0; i < scrlist.Count; i++)//保留每次进化产生的最优粒子
{
if (bestfit > scrlist[i].Fit)
{
bestfit = scrlist[i].Fit;
int[] a = new int[ConstNum.PARTICE_DIM];
for (int k = 0; k < ConstNum.PARTICE_DIM; k++)
{
a[k] = scrlist[i].getIndextask(k);
}
globalbest.setservers(a);
}
}
//选择
List <GA_Server> temp = new List <GA_Server>();
for (int i = 0; i < ConstNum.NP; i++)
{
temp.Add(new GA_Server());
}
double tfit = 0;
//scrlist=GA.GA_Sort_fitness(scrlist);
for (int i = 0; i < ConstNum.NP; i++)
{
int[] a = new int[ConstNum.PARTICE_DIM];
for (int k = 0; k < ConstNum.PARTICE_DIM; k++)
{
a[k] = scrlist[i].getIndextask(k);
}
temp[i].setservers(a);
temp[i].Fit = 1 / scrlist[i].Fit;
tfit += temp[i].Fit;
}
double tt = 0;
for (int i = 0; i < ConstNum.NP; i++) //两个for循环，轮盘赌选择
{
tt += temp[i].Fit;
temp[i].Fit = tt / tfit;
}
for (int i = 0; i < ConstNum.NP; i++)
{
double po;
int pos = 0, j;
po = rad.NextDouble();
for (j = 0; j < ConstNum.NP - 1; j++)
{
if (po < temp[j].Fit && j == 0)
{
pos = j;
}
else
{
if (po >= temp[j].Fit && po < temp[j + 1].Fit)
{
pos = j + 1;
break;
}
}
}
int[] a = new int[ConstNum.PARTICE_DIM];
for (int k = 0; k < ConstNum.PARTICE_DIM; k++)
{
a[k] = temp[pos].getIndextask(k);
}
dlist[i].setservers(a);
dlist[i].Fit = scrlist[pos].Fit;
}
//交叉:随机选择父体，进行交叉
//GA_Sort_fitness(scrlist);
int[] CrossoverNum = new int[(int)(ConstNum.crossover * ConstNum.NP)];
for (int i = 0; i < CrossoverNum.Length; i++)
{
int rad1, rad2, rad3;//rad1表示父本1;rad2表示父本2;rad3交叉位置
while (true)
{
rad1 = rad.Next(0, dlist.Count);
rad2 = rad.Next(0, dlist.Count);
if (rad1 != rad2)
{
break;
}
}
rad3 = rad.Next(0, ConstNum.PARTICE_DIM);
int a = 0;
for (int j = rad3; j < ConstNum.PARTICE_DIM; j++)
{
a = dlist[rad1].getIndextask(j);
dlist[rad1].setIndextask(j, dlist[rad2].getIndextask(j));
dlist[rad2].setIndextask(j, a);
}
}
//变异
for (int i = 0; i < (int)(ConstNum.Mutation * scrlist.Count); i++)
{
int rd1, rd2, rd3;//rd1表示待变异的算子编号;rd2表示变异的位置;rd3表示变异结果
rd1 = rad.Next(0, scrlist.Count);
rd2 = rad.Next(0, ConstNum.PARTICE_DIM);
rd3 = rad.Next(0, wlist[rd2].Count);
dlist[rd1].setIndextask(rd2, rd3);
}
//新种群产生
for (int i = 0; i < scrlist.Count; i++)
{
int[] a = new int[ConstNum.PARTICE_DIM];
for (int k = 0; k < ConstNum.PARTICE_DIM; k++)
{
a[k] = dlist[i].getIndextask(k);
}
scrlist[i].setservers(a);
}
}
fit = bestfit;
return(globalbest);
}