public void Crossover()
{
List<GA_chromosome> newChromPool = new List<GA_chromosome>();
while (chromPool.Count >= 2)
{
GA_chromosome PA = chromPool[rand.Next(chromPool.Count)];
chromPool.Remove(PA);
GA_chromosome PB = chromPool[rand.Next(chromPool.Count)];
chromPool.Remove(PB);
//Decide crossover
if (rand.Next(100) + 1 <= crossoverProbability * 100)
{
GA_chromosome CA = new GA_chromosome(phases, minGreen, maxGreen, roadInfos, reservationTimeEnable);
GA_chromosome CB = new GA_chromosome(phases, minGreen, maxGreen, roadInfos, reservationTimeEnable);
CA.SetFitnessWeight(Weight_IAWR, Weight_TDF, Weight_CLF);
CB.SetFitnessWeight(Weight_IAWR, Weight_TDF, Weight_CLF);
//Decide crossover point
int crossoverPoint = 0;
if (phases > 2)
{
crossoverPoint = rand.Next(phases - 1);
}
//Crossover start
for (int i = 0; i < phases; i++)
{
if (i <= crossoverPoint)
{
CA.SetGreen(i, PA.GetGreen(i));
CB.SetGreen(i, PB.GetGreen(i));
}
else
{
CA.SetGreen(i, PB.GetGreen(i));
CB.SetGreen(i, PA.GetGreen(i));
}
}
//Put child chromosome to new pool
newChromPool.Add(CA);
newChromPool.Add(CB);
}
else
{
//Put parent chromosome to new pool
newChromPool.Add(PA);
newChromPool.Add(PB);
}
}
chromPool = newChromPool;
}
public Dictionary<int, int> Optimize(Boolean cycleLengthFixed, int phases, int minGreen, int maxGreen, List<RoadInfo> roadInfos)
{
SetGAParametersByAIManager();
currentGeneration = 0;
bestChromosome = null;
optimizationRecords = new List<string>();
this.cycleLengthFixed = cycleLengthFixed;
this.phases = phases;
this.maxGreen = maxGreen;
this.minGreen = minGreen;
this.roadInfos = roadInfos;
//GA process
InitializePool();
do{
Reproduction_RestoreSeletedChro();
//Reproduction();
Crossover();
Mutation();
GenerateNewChromosome();
EvaluateFitness();
currentGeneration++;
}while (currentGeneration < generationLimit);
return bestChromosome.GetAllGreenTime();
}
public void GenerateNewChromosome()
{
int generatedQuantity = populationSize - chromPool.Count;
//Generate lack of chromosome, until satisfied the population size.
for (int i = 0; i < generatedQuantity; i++)
{
GA_chromosome newChrom = new GA_chromosome(phases, minGreen, maxGreen, roadInfos, reservationTimeEnable);
newChrom.SetFitnessWeight(Weight_IAWR, Weight_TDF, Weight_CLF);
chromPool.Add(newChrom);
}
}
public void InitializePool()
{
chromPool.Clear();
for (int i = 0; i < populationSize; i++)
{
GA_chromosome newChrom = new GA_chromosome(phases, minGreen, maxGreen, roadInfos, reservationTimeEnable);
newChrom.SetFitnessWeight(Weight_IAWR, Weight_TDF, Weight_CLF);
chromPool.Add(newChrom);
}
}
public void EvaluateFitness()
{
GA_chromosome bestChrom_currentPool = chromPool[0];
//Find best chromosome of this generation
foreach (GA_chromosome chrom in chromPool)
{
if (chrom.GetFitness() < bestChrom_currentPool.GetFitness())
{
bestChrom_currentPool = chrom;
}
}
//Compare the best chromosome of this generation and best chromosome of all generation,
//if this is first generation, set the best chromosome of this generation as the best chromesome of all generation.
if (bestChromosome == null || bestChrom_currentPool.GetFitness() < bestChromosome.GetFitness())
{
if (bestChromosome == null)
{
bestChromosome = new GA_chromosome(phases, minGreen, maxGreen, roadInfos, reservationTimeEnable);
bestChromosome.SetFitnessWeight(Weight_IAWR, Weight_TDF, Weight_CLF);
}
for (int p = 0; p < phases; p++)
{
bestChromosome.SetGreen(p, bestChrom_currentPool.GetGreen(p));
}
optimizationRecords.Add("Generation :" + currentGeneration + " Chromosome : " + bestChromosome.PrintChromosome() + " fitness : " + bestChromosome.GetFitness());
}
}