public Population oddCross(Random r1, Population P2, int size, int count_row, int n) //Number of individuals is an odd number
{
Crossover CO2 = new Crossover();
DesignPlan[] designplans = new DesignPlan[size];
designplans[0] = P2.DP[0];
designplans[1] = P2.DP[1];
s = (size - 1) / 2;
for (int i = 1; i < s; i++)
{
int p = r1.Next(10 * count_row); //To gene length
int a = i * 2, //Odd-numbered
b = a + 1; //Even-numbered
DesignPlan[] designplan = CO2.Cross1(P2.DP[a], P2.DP[b], p, count_row);
designplans[a] = designplan[0];
designplans[b] = designplan[1];
}
int p2 = r1.Next(10 * count_row);//To gene length
DesignPlan[] designplan2 = CO2.Cross1(P2.DP[size - 1], P2.DP[0], p2, count_row);
designplans[size - 1] = designplan2[0];
Population population = new Population(designplans, size, n);
return(population);
}
public Population evenCross(Random r1, Population P2, int size, int count_row, int n) //Number of individuals is an even number
{
s = size / 2;
Crossover CO2 = new Crossover();
DesignPlan[] designplans = new DesignPlan[size];
designplans[0] = P2.DP[0];
designplans[1] = P2.DP[1];
for (int i = 1; i < s; i++) //Crossover by performing, generating odd-numbered and even-numbered two designplans for loop once
{
int p = r1.Next(10 * count_row); //To gene length
int a = i * 2, //Odd-numbered
b = a + 1; //Even-numbered
DesignPlan[] designplan = CO2.Cross1(P2.DP[a], P2.DP[b], p, count_row);
designplans[a] = designplan[0];
designplans[b] = designplan[1];
}
Population population = new Population(designplans, size, n);
return(population);
}