/// <summary>
/// 获得当前最优解
/// </summary>
/// <param name="cukoo"></param>
/// <returns></returns>
public Cukoo GetBestNest(Cukoo cukoo)
{
double fitall = 0;
for (int i = 0; i < cukoo.Nest.GetLength(0); i++)
{
double temp1 = FitNess(DimensionalityReduction(cukoo.Nest, i));
double temp2 = FitNess(DimensionalityReduction(cukoo.newNest, i));
if (temp1 > temp2)
{
//old origin 无必要修改
cukoo.Nest = SetupDimensionalArray(cukoo.Nest, cukoo.newNest, i);
if (temp2 < cukoo.NBest)
{
cukoo.NBest = temp2;
cukoo.NestBest = SetupArray(cukoo.NestBest, cukoo.Nest, i);
fitall = fitall + temp2;
}
}
else
{
fitall = fitall + temp1;
}
var meanfit = DimensionalityReduction(cukoo.Nest, 0);
cukoo.NestBest = meanfit.Select(x => (fitall / x)).ToArray();
}
return(cukoo);
}
/// <summary>
/// 布谷鸟算法
/// </summary>
/// <param name="lamuda"></param>
/// <param name="pa"></param>
/// <returns></returns>
public double GetCs(double lamuda = 1, double pa = 0.25)
{
int[] lb = { -5, -5 };
int[] ub = { 5, 5 };
int populationSize = 20;
int dim = 2;
double[,] arrTemp = new double[populationSize, dim];
double[,] nest = GetRandomDimensionalArray(arrTemp, lb[0], ub[0]);
double[] nestBest = DimensionalityReduction(nest, 0);
double nBest = FitNess(nestBest);
Cukoo cukoo = new Cukoo()
{
Nest = nest,
NBest = nBest,
NestBest = nestBest,
newNest = nest
};
cukoo = GetBestNest(cukoo);
for (int i = 0; i < 30; i++)
{
double[,] nestC = new double[cukoo.Nest.GetLength(0), cukoo.Nest.GetLength(1)];
Array.Copy(cukoo.Nest, nestC, cukoo.Nest.Length);
//根据莱维飞行产生新的位置
cukoo.newNest = GetNewNestVialevy(nestC, cukoo.NestBest, lb, ub, lamuda);
//判断新的位置优劣进行替换
cukoo = GetBestNest(cukoo);
double[,] nestE = new double[cukoo.Nest.GetLength(0), cukoo.Nest.GetLength(1)];
Array.Copy(cukoo.Nest, nestE, cukoo.Nest.Length);
//丢弃部分巢穴
cukoo.newNest = EmptyNest(nestE, lb, ub, pa);
cukoo = GetBestNest(cukoo);
}
//最优解为 cukoo.NBest
return(cukoo.NBest);
}
