//评估高干扰小区以及关联小区集合总C2I干扰
public double checkhighlist(double delta2, List<int> highlist,Individual indiv)
{
int i=0;
int j=0;
double interftemp = 0;
//同频干扰
for (i = 0; i < highlist.Count; i++)
{
for (j = 0; j < slist.sectorList.Count; j++)
{
if (indiv.gene[highlist[i]] != -1 && indiv.gene[j] != -1)
{
//同频
if (indiv.gene[highlist[i]] == indiv.gene[j])
{
interftemp += slist.InterfMatrix[highlist[i], j];
interftemp += slist.InterfMatrix[j, highlist[i]];
}
else//异频
{
interftemp += slist.InterfMatrix[highlist[i], j] * delta2;
interftemp += slist.InterfMatrix[j, highlist[i]] * delta2;
}
}
}
}
return interftemp;
}
//评估整个个体（方案）的C2I干扰
public double check(double delta2,ref Individual indiv)
{
//计算初始的小区间同频以及异频干扰总和
int i=0;
int j=0;
double interftemp = 0;
//同频干扰
for (i = 0; i < slist.sectorList.Count; i++)
{
for (j = 0; j < slist.sectorList.Count; j++)
{
if (indiv.gene[i] != -1 && indiv.gene[j] != -1)
{
//同频
if (indiv.gene[i] == indiv.gene[j])
{
interftemp += slist.InterfMatrix[i, j];
}
else//异频
{
interftemp += slist.InterfMatrix[i, j] * delta2;
}
}
}
}
indiv.interf = interftemp;
return interftemp;
}
public void clone(ref Individual individual)
{
for (int i = 0; i < gene.Length; i++)
{
individual.gene[i] = gene[i];
}
individual.interf = interf;
}
//评估函数（上+下）
public double DownEvalueTotalFitness(int n, int k, Individual individual, List<int> highintefcelllist)
{
Individual tempindiv = new Individual(slist.sectorList.Count);
individual.clone(ref tempindiv);
int i = 0, j = 0;
int minindex = 0;
double minintfess = 0;
for (i = k + 1; i < n; i++)
{
for (j = 0; j < slist.sectorList[highintefcelllist[i]].useablefcn.Count; j++)
{
if (j == 0)
{
tempindiv.gene[highintefcelllist[i]] = slist.sectorList[highintefcelllist[i]].useablefcn[j];
minindex = 0;
minintfess = checkhighlist(delta2, highintefcelllist,tempindiv);
}
else
{
tempindiv.gene[highintefcelllist[i]] = slist.sectorList[highintefcelllist[i]].useablefcn[j];
double tempinter = checkhighlist(delta2, highintefcelllist, tempindiv);
if (tempinter < minintfess)
{
minintfess = tempinter;
minindex = j;
}
}
}
tempindiv.gene[highintefcelllist[i]] = slist.sectorList[highintefcelllist[i]].useablefcn[minindex];
}
return checkhighlist(delta2,highintefcelllist,tempindiv);
}
//数据的预处理
private void prepareData(string configFile)
{
XML xml = new XML(configFile);
DB db = new DB("Configuration/Database");
try
{
#region ；从 配置文件 获取 数据库配置信息 ；并连接数据库
if (db.initialize(xml) == false)
{
Console.WriteLine("初始化配置文件错误！");
return;
}
if (db.GetConnection() == null)
{
Console.WriteLine("连接数据库错误！");
return;
}
#endregion
slist = new SectorList("Configuration/SqlInitSectorInfoof37900", "Configuration/SqlInitSectorInfoof38098", "Configuration/SqlInitInterfInfo");
#region ；从 配置文件 获取 小区列表 各项信息；
if (slist.initialize(db, xml) == false)
{
Console.WriteLine("初始化数据错误！");
return;
}
ancestor = new Individual(slist.sectorList.Count);
ancestorori = new Individual(slist.sectorList.Count);
for (int i = 0; i < slist.sectorList.Count; i++)
{
ancestor.gene[i] = slist.sectorList[i].FCN;
ancestorori.gene[i] = slist.sectorList[i].FCN;
}
#endregion
}
catch (Exception e)
{
Console.WriteLine("PREPARE ERR: {0}!", e.Message);
}
finally
{
db.close();
xml.Dispose();
}
}
//分支界限法搜索频点序列
public void SearchBetter2(List<int> highintefcelllist)
{
System.Diagnostics.Stopwatch Time = new System.Diagnostics.Stopwatch();
Time.Start();
Individual indiv = new Individual(slist.sectorList.Count);
ancestor.clone(ref indiv);
double interftempori = checkhighlist(delta2,highintefcelllist,indiv);
for (int i = 0; i < highintefcelllist.Count; i++)
{
indiv.gene[highintefcelllist[i]] = -1;
}
int k = 0;// 小区下标
int n = highintefcelllist.Count;//小区个数
int[] fcnindex = new int[n];
int[] x = new int[n];
for (int j = 0; j < n; j++)
{
fcnindex[j] = -1;
}
int count = 0;
int index = 0;
//按照层次，横向搜索
for (int ii = 0; ii < n; ii++)
{
double minfitness = 0;
int minfitnessindex = 0;
bool first = true;
for (index = 0; index < slist.sectorList[highintefcelllist[ii]].useablefcn.Count; index++)
{
count++;
x[ii] = slist.sectorList[ii].useablefcn[index];
if (checkhighlist(delta2, highintefcelllist, indiv) < interftempori)//可以加条件,剪枝,保证个体条件不恶化
{
indiv.gene[highintefcelllist[ii]] = x[ii];
if (first)
{
//评估函数（上界+下界），这里是按照干扰来评估的。
minfitness = DownEvalueTotalFitness(n, ii, indiv, highintefcelllist);
minfitnessindex = index;
first = false;
}
else
{
double temp = DownEvalueTotalFitness(n, ii, indiv, highintefcelllist);
if (temp < minfitness)
{
minfitness = temp;
minfitnessindex = index;
}
}
}//if
indiv.gene[highintefcelllist[ii]] = -1;
}//for
x[ii] = slist.sectorList[ii].useablefcn[minfitnessindex];
indiv.gene[highintefcelllist[ii]] = x[ii];
if (checkhighlist(delta2, highintefcelllist, indiv) > interftempori)
{
Console.WriteLine("到达第"+ii+"个小区最优解方向就已经停止,没搜到，一共用时 {0}", Time.Elapsed.TotalSeconds);
break;
}
}//for
double t=checkhighlist(delta2,highintefcelllist,indiv);
if (t<=interftempori)//最后筛选的条件,选择满足什么样条件的个体
{
indiv.clone(ref ancestor);
Time.Stop();
Console.WriteLine("已经搜到，一共用时 {0}S,干扰小区和关联小区集合一共提高{1}", Time.Elapsed.TotalSeconds,(interftempori-t)/interftempori*100+"%");
}
else
{
Time.Stop();
Console.WriteLine("没有搜到，一共用时 {0}S", Time.Elapsed.TotalSeconds);
}
}
//回朔法搜索频点序列
public bool SearchBetter(List<int> highintefcelllist)
{
System.Diagnostics.Stopwatch Time1 = new System.Diagnostics.Stopwatch();
Time1.Start();
Individual indiv = new Individual(slist.sectorList.Count);
ancestor.clone(ref indiv);
double interftempori = checkhighlist(delta2, highintefcelllist, ancestor);
double orihighlist = interftempori;
for (int i = 0; i < highintefcelllist.Count; i++)
{
indiv.gene[highintefcelllist[i]] = -1;
}
int k = 0;// 小区下标
int n = highintefcelllist.Count;//小区个数
int[] fcnindex = new int[n];
for (int j = 0; j < n; j++)
{
fcnindex[j] = -1;
}
//这是主要的回朔
bool flag = false;
int count = 0;
int deletecount = 0;
int solutioncount = 0;
while (k >= 0 && Time1.Elapsed.TotalSeconds <= 300)//&& Time.Elapsed.TotalSeconds <= 300
{
fcnindex[k]++;
indiv.gene[highintefcelllist[k]] = -1;
if (fcnindex[k] < slist.sectorList[highintefcelllist[k]].useablefcn.Count)
{
indiv.gene[highintefcelllist[k]] = slist.sectorList[highintefcelllist[k]].useablefcn[fcnindex[k]];
count++;
}
else
{
fcnindex[k] = -1;//重新置空PCI；列表下标，这里出了问题以前！
k = k - 1;//回朔到上一个小区
continue;
}
//其中OK函数负责找到PCI，并且实际分配
while (checkhighlist(delta2, highintefcelllist, indiv) > interftempori)//可以加其他条件
{
fcnindex[k]++;
deletecount++;
if (fcnindex[k] < slist.sectorList[highintefcelllist[k]].useablefcn.Count)
{
indiv.gene[highintefcelllist[k]] = slist.sectorList[highintefcelllist[k]].useablefcn[fcnindex[k]];//继续找下一个可用PCI
count++;
}
else
{
break;
}
}
if (fcnindex[k] < slist.sectorList[highintefcelllist[k]].useablefcn.Count)
{
if (k == n - 1)
{
double tempinterf = checkhighlist(delta2, highintefcelllist, indiv);
if (tempinterf < interftempori)
{
interftempori = tempinterf;
indiv.clone(ref ancestor);
solutioncount++;
flag = true;
Console.WriteLine("高干扰小区以及关联小区一共提升了" + (orihighlist - interftempori) / orihighlist * 100 + "%");
continue;
}
else
{
continue;
}
}
else
{
k = k + 1;//分配下一个PCI
}
}
else
{
fcnindex[k] = -1;//重新置空PCI；列表下标，这里出了问题以前！
indiv.gene[highintefcelllist[k]] = -1;
k = k - 1;//回朔到上一个小区
}
}
if (flag)
{
Console.WriteLine("搜索节点个数为:" + count + "剪枝个数为:" + deletecount + "解的个数为:" + solutioncount);
return true;
}
else
{
Console.WriteLine("搜索节点个数为:" + count + "剪枝个数为:" + deletecount + "解的个数为:" + solutioncount);
return false;
}
}
