public DesignPlan mutation(Random r1, DesignPlan DP, int count_row)//Mutation
{
n = 10 * count_row;
odd = r1.Next(100);
if (odd <= 2)//3% mutation rate
{
for (int i = 0; i < n; i++)
{
if (r1.Next(100) < 3)//Mutation rate for one gene 3%
{
if (DP.Chromo.genes[i] == 0)
{
DP.Chromo.genes[i] = 1;
}
else
{
DP.Chromo.genes[i] = 0;
}
}
}
return(DP);
}
else
{
return(DP);
}
}
public DesignPlan graetmutation(Random r1, DesignPlan DP, int count_row) // Large Mutation
{
n = 10 * count_row; //Gene Length
odd = r1.Next(100);
if (odd <= 50)
{
for (int i = 0; i < n; i++)
{
if (r1.Next(100) < 50)//Mutation rate for one gene 50%
{
if (DP.Chromo.genes[i] == 0)
{
DP.Chromo.genes[i] = 1;
}
else
{
DP.Chromo.genes[i] = 0;
}
}
}
return(DP);
}
else
{
return(DP);
}
}
public void Best(int count_row, int g_size, Piping_System piping) //Selection of the best individuals from the population
{
double F = 100000; //Evaluation Value
double F2 = 100000;
int A = 0;
int B = 0;
for (int i = 0; i < size; i++)
{
double fit = designplans[i].Fittness(count_row, g_size, piping);
if (fit < F)
{
F = fit;
B = A;
A = i;
}
else if (fit < F2)
{
F2 = fit;
B = i;
}
}
best = designplans[A];
second = designplans[B];
}
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);
}
public void Elite(Population original, int count_row, Deck[] deck_all, Cluster cluster_GA) //Elite Selection
{
DesignPlan DP1 = new DesignPlan(count_row);
designplans[0] = DP1;
DesignPlan DP2 = new DesignPlan(count_row);
designplans[1] = DP2;
designplans[0].Chromo.genes = original.B.Chromo.genes;
designplans[0].makeDesignplan2(count_row, deck_all, cluster_GA);
designplans[1].Chromo.genes = original.S.Chromo.genes;
designplans[1].makeDesignplan2(count_row, deck_all, cluster_GA);
}
public DesignPlan M(Random r1, DesignPlan C, int aa, int count_row)
{
int a = (aa) % 50;//Cause once large mutation in 50 generations
if (a == 0)
{
DesignPlan chromosome = graetmutation(r1, C, count_row);
return(chromosome);
}
else
{
DesignPlan chromosome = mutation(r1, C, count_row);
return(chromosome);
}
}
public Population Mutation(Random r1, Population P, int count_row)// Mutation
{
Mutation DM = new Mutation();
DesignPlan[] DP1 = new DesignPlan[size];
DP1[0] = P.DP[0];
DP1[1] = P.DP[1];
for (int i = 2; i < size; i++)
{
DesignPlan DP2 = DM.M(r1, P.DP[i], n, count_row);
DP1[i] = DP2;
}
Population P3 = new Population(DP1, size, n);
return(P3);
}
public DesignPlan selectMember(Random r1, DesignPlan[] original, int count_row) //Selection from 2 individuals
{
DesignPlan DP = new DesignPlan(count_row);
int a = r1.Next(size);
int b = r1.Next(size);
if (original[a].Fit < original[b].Fit)
{
DP.Chromo.genes = original[a].Chromo.genes;
return(DP);
}
else
{
DP.Chromo.genes = original[b].Chromo.genes;
return(DP);
}
}
public void makePopulaiton1(Deck[] deck_GA, int count_row, Cluster cluster_GA, Random r1, Piping_System piping_GA) //First Generation
{
designplans = new DesignPlan[size];
for (int i = 0; i < size; i++) //size: generation size
{
DesignPlan C1 = new DesignPlan(count_row);
C1.makeDesignplan1(count_row, r1, cluster_GA, deck_GA);
designplans[i] = C1;
//-----------designplans[i] Initialize after Generation, The deck Information---------------
Deck deck = new Deck();
deck.Initialize(deck_GA);
//------------------------------------------------------------------------
}
}
public DesignPlan[] Cross1(DesignPlan DP1, DesignPlan DP2, int p, int count_row)//1-point crossover
{
DesignPlan[] designplan = new DesignPlan[2];
DesignPlan designplan1 = new DesignPlan(count_row);
DesignPlan designplan2 = new DesignPlan(count_row);
for (int i = 0; i < p; i++)
{
designplan1.Chromo.genes[i] = DP1.Chromo.genes[i];
designplan2.Chromo.genes[i] = DP2.Chromo.genes[i];
}
for (int i = p; i < 10 * count_row; i++)//i is range for gene length
{
designplan1.Chromo.genes[i] = DP2.Chromo.genes[i];
designplan2.Chromo.genes[i] = DP1.Chromo.genes[i];
}
designplan[0] = designplan1;
designplan[1] = designplan2;
return(designplan);
}
