//Generate new population from current population
public static Population genNewPop(Population currentPopulation)
{
List <Tour> newPop = new List <Tour>();
//Perform Elitism, that means 10% of fittest population goes to next generation
int k = (Env.ELITISM * Env.POPULATION_SIZE / 100);
for (int i = 0; i < k; i++)
{
newPop.Add(currentPopulation.p[i]);
}
//Remaing 90% of next generation is produced by offspring
int j = ((100 - Env.ELITISM) * Env.POPULATION_SIZE / 100);
// From 50% of fittest population, chromosome will mate to produce offspring
for (int i = 0; i < j; i++)
{
int randNo = Program.r.Next(0, Env.POPULATION_SIZE / 2);
Tour parent1 = currentPopulation.p[randNo];
randNo = Program.r.Next(0, Env.POPULATION_SIZE / 2);
Tour parent2 = currentPopulation.p[randNo];
Tour offspring = parent1.mate(parent2);
//Probability that the new offspring has mutation
offspring = offspring.mutate_genes();
newPop.Add(offspring);
}
return(new Population(newPop));
}
//REMOVE DUPLICATION OF CHROMOSOME
public static Population removeDuplication(Population pop)
{
//Remove chromosome duplication by checking fitness
List <Tour> RemoveDuplication = pop.p.GroupBy(x => x.Fitness).Select(x => x.First()).ToList();
while (RemoveDuplication.Count < Env.POPULATION_SIZE)
{
//Crossover new offspring to replace the duplicated chromosome
int len = RemoveDuplication.Count;
int randNo = Program.r.Next(0, len - 1);
Tour parent1 = pop.p[randNo];
randNo = Program.r.Next(0, len - 1);
Tour parent2 = pop.p[randNo];
Tour offspring = parent1.mate(parent2);
offspring = offspring.mutate_genes();
RemoveDuplication.Add(offspring);
}
return(new Population(RemoveDuplication));
}
