// Update fitness
public bool UpdateFitness()
{
double fitness = 0.0, averageFitness = 0.0;
int index = -1;
for (int i = 0; i < _populationsize; ++i)
{
fitness = Fitness(_population[i]);
averageFitness += fitness;
if (_bestFitness < fitness)
{
_bestFitness = fitness;
index = i;
}
else
{
}
}
if (_bestAverageFitness < averageFitness && index >= 0)
{
_bestAverageFitness = averageFitness;
_bestSolution = DataCentre.DeepCopy(_population[index]);
return(true);
}
else
{
}
return(false);
}
//////////////////////////////////////////////////////////////////////////
// Visualization Tab
// Problem to Static Chart for number of online and offline virtual machines
public void Problem2StaticChart(DataCentre iDataCentre, ref Chart chart)
{
List <Variation> iObjects = iDataCentre._variations;
chart.Series[0].Points.Clear();
chart.Series[1].Points.Clear();
for (int i = 0; i < iObjects.Count; ++i)
{
chart.Series[0].Points.Add(new DataPoint(iObjects[i]._time,
iObjects[i]._vmsoff.Count));
chart.Series[1].Points.Add(new DataPoint(iObjects[i]._time, -
iObjects[i]._vmson.Count));
}
chart.ChartAreas[0].AxisX.Maximum = iDataCentre._duration;
}
// Evolve the GA population
public void Evolve()
{
while (_noupdate < _termination)
{
int[][] newpopulation = DataCentre.DeepCopy(_population);
for (int i = 0; i < _populationsize; ++i)
{
DataCentre._random = new Random((int)DateTime.Now.Ticks);
if (DataCentre._random.NextDouble() <= _pcrossover)
{
int j = Selection(i);
int[] child = CrossOver(_population[i], _population[j]);
if (Fitness(child) > Fitness(newpopulation[i]))
{
newpopulation[i] = child;
}
else
{
}
}
else
{
}
DataCentre._random = new Random((int)DateTime.Now.Ticks);
if (DataCentre._random.NextDouble() <= _pmutation)
{
newpopulation[i] = Mutation(newpopulation[i]);
}
else
{
}
}
_population = DataCentre.DeepCopy(newpopulation);
if (UpdateFitness())
{
_noupdate = 0;
}
else
{
++_noupdate;
}
}
}