/*
* "Main" function of the program. It runs for the entire generation count, generating children,
* culling the population, and outputting the stats.
*/
public void run()
{
string parent1;
string parent2;
string child;
Money coinList = new Money();
for (int i = 0; i < numberOfVariables; i++) //Get the input
{
getInput(i);
}
initialize(); //Initialize the population
for (int genCount = 0; genCount < generations; genCount++)
{
newPopValues(); //update the population values.
survivorCount = 0;
for (int childrenCount = 0; childrenCount < numOfChildren; childrenCount++)
{
// Select 2 Random Parents, perform crossover
parent1 = population[rand.Next() % popSize];
parent2 = population[rand.Next() % popSize];
child = crossover(parent1, parent2); //random position, front half of a goes to child, back half of b goes to child
if ((rand.Next() % 100) < mutationRate) //percentage of chance for mutation
child = mutate(child); //pick random spot, replace value with new random value
// evaluate child
values[popSize + childrenCount] = coinList.getValue(child);
fitness[popSize + childrenCount] = evaluateFitness(values[popSize + childrenCount]);
// add child to population
population[popSize + childrenCount] = child;
}
//sort population by fitness
sort(0, fitness.Count - 1);
//elitism - copies certain number of top choices to survivors
elitistSelection();
//survivor selection - tournament (do until survivor is filled)
while (survivorCount < popSize)
{
survivors[survivorCount] = population[tournamentSelection()];
survivorCount++;
}
//population = survivors
for (int i = 0; i < survivorCount; i++)
{
population[i] = survivors[i];
}
//report stats - best individual, average fitness level
outputStats(genCount);
}
//Memory Management
population.Clear();
values.Clear();
survivors.Clear();
fitness.Clear();
}
/*
* This function is called to compute the values and the fitness of the
* population size.
*/
void newPopValues()
{
Money coinList = new Money();
for (int index = 0; index < popSize; index++)
{
values[index] = coinList.getValue(population[index]);
fitness[index] = evaluateFitness(values[index]);
}
}
/*
* Function called to initialize all of the variables to valid states.
* It will also generate a random starting string for each population
* index.
*/
void initialize()
{
Money coinList = new Money();
for (int i = 0; i < popSize + numOfChildren; i++)
{
population.Add( coinList.generateRandomCoinList(numOfCoins) ); //create a new randomg coin list
survivors.Add("");
values.Add(0.00);
fitness.Add(0.00);
}
}
