/* Routine for two point binary Crossover */
static void BinaryCrossover(Individual parent1, Individual parent2, Individual child1, Individual child2, ProblemDefinition problemObj, Randomization randomizationObj)
{
int i, j;
double rand;
int temp, site1, site2;
for (i = 0; i < problemObj.BinaryVariableCount; i++)
{
rand = randomizationObj.RandomPercent();
if (rand <= problemObj.BinaryCrossoverProbability)
{
problemObj.BinaryCrossoverCount++;
site1 = randomizationObj.RandomInteger(0, problemObj.Nbits[i] - 1);
site2 = randomizationObj.RandomInteger(0, problemObj.Nbits[i] - 1);
if (site1 > site2)
{
temp = site1;
site1 = site2;
site2 = temp;
}
for (j = 0; j < site1; j++)
{
child1.Gene[i][j] = parent1.Gene[i][j];
child2.Gene[i][j] = parent2.Gene[i][j];
}
for (j = site1; j < site2; j++)
{
child1.Gene[i][j] = parent2.Gene[i][j];
child2.Gene[i][j] = parent1.Gene[i][j];
}
for (j = site2; j < problemObj.Nbits[i]; j++)
{
child1.Gene[i][j] = parent1.Gene[i][j];
child2.Gene[i][j] = parent2.Gene[i][j];
}
}
else
{
for (j = 0; j < problemObj.Nbits[i]; j++)
{
child1.Gene[i][j] = parent1.Gene[i][j];
child2.Gene[i][j] = parent2.Gene[i][j];
}
}
}
}
/* Actual implementation of the randomized quick sort used to sort a population based on a particular objective chosen */
static void q_sort_front_obj(Population pop, int objcount, int[] objArray, int left, int right, Randomization randomizationObj)
{
int index;
int temp;
int i, j;
double pivot;
if (left < right)
{
index = randomizationObj.RandomInteger(left, right);
temp = objArray[right];
objArray[right] = objArray[index];
objArray[index] = temp;
pivot = pop.IndList[objArray[right]].Obj[objcount];
i = left - 1;
for (j = left; j < right; j++)
{
if (pop.IndList[objArray[j]].Obj[objcount] <= pivot)
{
i += 1;
temp = objArray[j];
objArray[j] = objArray[i];
objArray[i] = temp;
}
}
index = i + 1;
temp = objArray[index];
objArray[index] = objArray[right];
objArray[right] = temp;
q_sort_front_obj(pop, objcount, objArray, left, index - 1, randomizationObj);
q_sort_front_obj(pop, objcount, objArray, index + 1, right, randomizationObj);
}
}
/* Routine for Tournament Selection, it creates a newPopulation from oldPopulation by performing Tournament Selection and the Crossover */
static void Selection(Population oldPopulation, Population newPopulation, ProblemDefinition problemObj, Randomization randomizationObj)
{
int[] a1, a2; //todo: optmizasyon
int temp;
int i;
int rand;
Individual parent1, parent2;
a1 = new int[problemObj.PopulationSize];
a2 = new int[problemObj.PopulationSize];
for (i = 0; i < problemObj.PopulationSize; i++)
{
a1[i] = a2[i] = i;
}
for (i = 0; i < problemObj.PopulationSize; i++)
{
rand = randomizationObj.RandomInteger(i, problemObj.PopulationSize - 1);
temp = a1[rand];
a1[rand] = a1[i];
a1[i] = temp;
rand = randomizationObj.RandomInteger(i, problemObj.PopulationSize - 1);
temp = a2[rand];
a2[rand] = a2[i];
a2[i] = temp;
}
for (i = 0; i < problemObj.PopulationSize; i += 4)
{
parent1 = Tournament(oldPopulation.IndList[a1[i]], oldPopulation.IndList[a1[i + 1]], problemObj, randomizationObj);
parent2 = Tournament(oldPopulation.IndList[a1[i + 2]], oldPopulation.IndList[a1[i + 3]], problemObj, randomizationObj);
Crossover(parent1, parent2, newPopulation.IndList[i], newPopulation.IndList[i + 1], problemObj, randomizationObj);
parent1 = Tournament(oldPopulation.IndList[a2[i]], oldPopulation.IndList[a2[i + 1]], problemObj, randomizationObj);
parent2 = Tournament(oldPopulation.IndList[a2[i + 2]], oldPopulation.IndList[a2[i + 3]], problemObj, randomizationObj);
Crossover(parent1, parent2, newPopulation.IndList[i + 2], newPopulation.IndList[i + 3], problemObj, randomizationObj);
}
}
/* Actual implementation of the randomized quick sort used to sort a population based on crowding distance */
static void q_sort_dist(Population pop, int[] dist, int left, int right, Randomization randomizationObj)
{
int index;
int temp;
int i, j;
double pivot;
if (left < right)
{
index = randomizationObj.RandomInteger(left, right);
temp = dist[right];
dist[right] = dist[index];
dist[index] = temp;
pivot = pop.IndList[dist[right]].CrowdDist;
i = left - 1;
for (j = left; j < right; j++)
{
if (pop.IndList[dist[j]].CrowdDist <= pivot)
{
i += 1;
temp = dist[j];
dist[j] = dist[i];
dist[i] = temp;
}
}
index = i + 1;
temp = dist[index];
dist[index] = dist[right];
dist[right] = temp;
q_sort_dist(pop, dist, left, index - 1, randomizationObj);
q_sort_dist(pop, dist, index + 1, right, randomizationObj);
}
}
