public void GA1_DoWork(object sender, DoWorkEventArgs e)
{
try
{
watch.Start();
for (int gen = 0; gen < generations; gen++)//generations
{
if (GA1.CancellationPending == true)
{
return;
}
etilism1();//etilism
for (int i = 2; i < popsize; i += 2)
{
genome parent1 = selection1(); //select parent1
genome parent2 = selection1(); //select parent2
genome[] children = crossover(parent1, parent2); //crossover
children[0] = mutate(children[0]); //mutate 1st child
children[1] = mutate(children[1]); //mutate 2nd child
storenewpop1(children[0]); //store 1st child
storenewpop1(children[1]); //store 2nd child
}
setcurrpop1();
GA1.ReportProgress(gen, PresentPopData1);
Thread.Sleep(pause);
}
bestsoln1();
}
catch (Exception f)
{
MessageBox.Show(f.Message, "Something went wrong", MessageBoxButton.OK);
}
}
//crossover
private genome[] crossover(genome parent1, genome parent2)
{
Random k = new Random();
int h = k.Next(1, this.cities.Count - 2);
genome[] children = new genome[2];
children[0] = new genome();
children[1] = new genome();
if (crossoverrandom.NextDouble() < crossoverrate)
{
for (int i = 0; i < h; i++)//copy first parts of parent 1 to child 1
{
children[0].order.Add(parent1.order[i]);
}
for (int i = h; i < this.cities.Count; i++)//copy second part of parent 2 to child 2
{
children[1].order.Add(parent2.order[i]);
}
for (int i = 0; i < parent2.order.Count; i++) //fill up child 1
{
bool found = false;
for (int j = 0; j < children[0].order.Count; j++)
{
if (parent2.order[i] == children[0].order[j])
{
found = true;
break;
}
}
if (found == false)
{
children[0].order.Add(parent2.order[i]);
}
}
for (int i = 0; i < parent1.order.Count; i++)//fill up child 2
{
bool found = false;
for (int j = 0; j < children[1].order.Count; j++)
{
if (parent1.order[i] == children[1].order[j])
{
found = true;
break;
}
}
if (found == false)
{
children[1].order.Add(parent1.order[i]);
}
}
return(children);
}
else
{
children[0] = parent1;
children[1] = parent2;
return(children);
}
}
//select random start population
private void startpop1()
{
PresentPopData1.Clear();
NewPopData1.Clear();
genome g = new genome();
for (int i = 0; i < this.cities.Count; i++)
{
g.order.Add(i);
}
g.distance = genomefitness(g);
g.makestring();
PresentPopData1.Add(g);
g = null;
g = new genome();
g.distance = 0;
if (this.cities.Count % 2 == 0)
{
for (int i = this.cities.Count / 2; i < this.cities.Count; i++)
{
g.order.Add(i);
}
for (int i = (this.cities.Count / 2) - 1; i > -1; i--)
{
g.order.Add(i);
}
}
else
{
for (int i = this.cities.Count + 1 / 2; i < this.cities.Count; i++)
{
g.order.Add(i);
}
for (int i = (this.cities.Count + 1 / 2) - 1; i > -1; i--)
{
g.order.Add(i);
}
}
g.makestring();
g.distance = genomefitness(g);
PresentPopData1.Add(g);
Random m = new Random();
for (int i = 2; i < popsize; i++)
{
g = new genome();
int[] array = randomarray(m);
for (int k = 0; k < this.cities.Count; k++)
{
g.order.Add(array[k]);
}
g.distance = genomefitness(g);
g.makestring();
PresentPopData1.Add(g);
}
}
//get total distance of a genome
private int genomefitness(genome h)
{
int m = 0;
for (int i = 0; i < this.cities.Count; i++)
{
if (i + 1 == this.cities.Count)
{
m += distances[h.order[i], h.order[0]];
break;
}
m += distances[h.order[i], h.order[i + 1]];
}
return(m);
}
void GA_DoWork(object sender, DoWorkEventArgs e)
{
try
{
for (int gen = 0; gen < generations; gen++)//generations
{
if (GA.CancellationPending)
{
break;
}
while (NewPopData.Count > 0)
{
NewPopData.Clear();
}
etilism();//etilism
for (int i = 2; i < popsize; i += 2)
{
genome parent1 = selection(); //select parent1
genome parent2 = selection(); //select parent2
genome[] children = crossover(parent1, parent2); //crossover
children[0] = mutate(children[0]); //mutate 1st child
children[1] = mutate(children[1]); //mutate 2nd child
storenewpop(children[0]); //store 1st child
storenewpop(children[1]); //store 2nd child
Thread.Sleep(pause);
}
while (PresentPopData.Count > 0)
{
PresentPopData.Clear();
}
setcurrpop();
while (NewPopData.Count > 0)
{
NewPopData.Clear();
}
bestsoln();
this.GA.ReportProgress(gen);
Thread.Sleep(pause);
}
}
catch (Exception ex)
{
MessageBox.Show("Please run this input set without visualization" + " " + ex.Message, "Alert", MessageBoxButton.OK);
}
}
//mutate
private genome mutate(genome child)
{
Random d = new Random();
int num1 = d.Next(0, child.order.Count - 1);
int num2 = 0;
do
{
num2 = d.Next(0, child.order.Count - 1);
} while (num1 == num2);
if (mutaterandom.NextDouble() < mutationrate)
{
int temp = child.order[num1];
child.order[num1] = child.order[num2];
child.order[num2] = temp;
}
child.distance = genomefitness(child);
child.makestring();
return(child);
}
//store to new population
private void storenewpop1(genome newgenome)
{
NewPopData1.Add(newgenome);
}
