public reference Crossover(reference pParentA, reference pParentB, string pSecret_Phrase)
{
int crossover_point;
lock (syncLock)
crossover_point = random.Next(pParentA.phrase.Length);
reference tempChild = new reference(pSecret_Phrase);
for (int i = 0; i < crossover_point; i++)
{
tempChild.phrase[i] = pParentA.phrase[i];
}
for (int i = crossover_point; i < pParentA.phrase.Length; i++)
{
if (pParentA.phrase[i] != pSecret_Phrase[i])
{
tempChild.phrase[i] = pParentB.phrase[i];
}
else
{
tempChild.phrase[i] = pParentA.phrase[i];
}
}
var fitness = Fitness(tempChild.phrase, pSecret_Phrase);
tempChild.fitness = fitness;
return(tempChild);
}
public reference Generate(string pSecret_Phrase)
{
//genes = new char[pSecret_Phrase.Length];
//string chars = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789 ";
//string chars = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz ";
// to generate elete solution
CharDictionary = CountLetters(pSecret_Phrase);
int position = 0;
char[] new_phrase = new char[pSecret_Phrase.Length];
for (int j = 0; j < CharDictionary.Count; j++)
{
char key = CharDictionary.Keys.ElementAt(j);
int value = CharDictionary.Values.ElementAt(j);
for (int k = 0; k < value; k++)
{
lock (syncLock)
position = random.Next(pSecret_Phrase.Length);
if (new_phrase[position] == '\0')
{
new_phrase[position] = key;
}
else
{
int count = 0;
bool flag = true;
while (flag)
{
if (new_phrase[count] == '\0')
{
new_phrase[count] = key;
flag = false;
}
count++;
}
}
}
}
reference tempRef = new reference(pSecret_Phrase);
tempRef.phrase = new_phrase;
tempRef.fitness = Fitness(new_phrase, pSecret_Phrase);
return(tempRef);
}
private void Start_Click(object sender, RoutedEventArgs e)
{
SSMethods myssMethods = new SSMethods();
//1. generate inital solution & evaluate fitness of each solution
for (int i = 0; i < initialSolutionSize; i++)
{
InitialSolutions.Add(myssMethods.Generate(secret_phrase));
}
//2. apply improvment mehtod to solutions
myssMethods.ImprovementMethod(InitialSolutions, secret_phrase);
// evaluate fitness again
myssMethods.FitnessOfSet(InitialSolutions, secret_phrase);
// select best solutions set and make a reference set;
var InitialSolutionsOrdered = (from r in InitialSolutions
orderby r.fitness descending
select r).ToList();;
//3. create a reference set by taking top 20 from Initial Solution
for (int i = 0; i < referenceSetSize; i++)
{
// have to create a temp object othervise it is copied by ref not by value;
reference temp = new reference();
temp.fitness = InitialSolutionsOrdered[i].fitness;
temp.phrase = InitialSolutionsOrdered[i].phrase;
RefSet.Add(temp);
}
initialFitness = myssMethods.PointDistance(RefSet);
bool solution_not_found = true;
int iteration_count = 0;
int test_refupdate_count = 0;
while (iteration_count < maxIteration && solution_not_found)
{
//4. Crossover reference set
List <reference> Children = new List <reference>();
for (int i = 0; i < RefSet.Count; i++)
{
var ParentA = RefSet[i];
for (int j = i + 1; j < referenceSetSize; j++)
{
var tempChild = myssMethods.Crossover(ParentA, RefSet[j], secret_phrase);
Children.Add(tempChild);
}
}
myssMethods.ImprovementMethod(Children, secret_phrase);
myssMethods.FitnessOfSet(Children, secret_phrase);
var childrenInOrder = (from c in Children
orderby c.fitness descending
select c).ToList();
//5. update reference set with better fitness
for (int j = 0; j < referenceSetSize; j++)
{
bool flag = true;
int count = 0;
while (flag)
{
if (RefSet[j].fitness < childrenInOrder[count].fitness)
{
reference tempRef = new reference(secret_phrase);
tempRef.fitness = childrenInOrder[count].fitness;
tempRef.phrase = childrenInOrder[count].phrase;
RefSet[j].fitness = tempRef.fitness;
RefSet[j].phrase = tempRef.phrase;
childrenInOrder.RemoveAt(count);
test_refupdate_count++;
if (RefSet[j].fitness == 1)
{
solution_not_found = false;
}
flag = false;
}
count++;
if (count == childrenInOrder.Count)
{
flag = false;
}
}
}
iteration_count++;
}
//things to improve
//1. when the referense set stops updating, the we need to generate new Inital Solutions
//2. add initial solutions to reference set for deversification
//3. make sure that when crossing all letters are present in the phrase and not being excluded
// right now when crossing i loose some of letters
//4. improvement function is ok but can be so much better good , it just
double finalFitness = RefSet[0].fitness; //myssMethods.PointDistance(RefSet);
var refset_strings = myssMethods.getPhrase(RefSet);
//RefSet[0].fitness = 1;
double improvment = finalFitness - initialFitness;
int b = 0;
}
