public static Individ[] mate(Individ[] population , Random rand, int numParents)
{
Individ[] temp_Population = new Individ[population.Length];
//calculate parents
int parent1;
int parent2;
for (int i = 0; i < population.Length; i++)
{
parent1 = rand.Next(0, numParents);
parent2 = parent1;
//parent2 should not be like parent1
while(parent2 == parent1)
{
parent2 = rand.Next(0, numParents);
}
//if (i == 0)
//{
// temp_Population[i] = population[0];
//}
//else
//{
temp_Population[i] = procreation(population[parent1], population[parent2], rand);
//}
}
return temp_Population;
}
public async Task <IActionResult> Edit(int id, [Bind("Id,Idanimal,Name,Bio")] Individ individ)
{
if (id != individ.Id)
{
return(NotFound());
}
if (ModelState.IsValid)
{
try
{
_context.Update(individ);
await _context.SaveChangesAsync();
}
catch (DbUpdateConcurrencyException)
{
if (!IndividExists(individ.Id))
{
return(NotFound());
}
else
{
throw;
}
}
return(RedirectToAction(nameof(Index)));
}
return(View(individ));
}
protected override void OnCreate(Bundle savedInstanceState)
{
base.OnCreate(savedInstanceState);
string anchor = Intent.GetStringExtra("anchor");
this.SetContentView(Resource.Layout.individ_info);
DataBase db = new DataBase();
_ = db.CreateDataBaseAsync();
HttpClient client = new HttpClient();
Main main = GetMains(anchor, db, client);
Individ individ = GetIndivid(main.Idindivid, db, client);
animal = GetAnimal(individ.Idanimal, db, client);
IndividImages individImages = GetImages(individ.Id, db, client);
IndividInfo individInfo = new IndividInfo(individ, individImages);
IndividInfoAdapter adapter = new IndividInfoAdapter(this, new List <IndividInfo>()
{
individInfo
});
ListView.Adapter = adapter;
Button backButton = this.FindViewById <Button>(Resource.Id.BackButton);
backButton.Click += this.OnBackClick;
Button viewMoreButton = this.FindViewById <Button>(Resource.Id.ViewButton);
viewMoreButton.Click += this.OnViewClick;
}
public long StartAlgorithm(int generations, int sampleSize)
{
var generationNumber = 0;
Stopwatch watch = new Stopwatch();
watch.Start();
while (generations != generationNumber && Population.Fittest().Fitness != 0)
{
var newPopulation = new Individ[PopulationSize];
for (var i = 0; i < PopulationSize; i += 2)
{
var siblings = Crossover(Sample(sampleSize));
newPopulation[i] = siblings.Item1;
newPopulation[i + 1] = siblings.Item2;
}
Population.Individs = newPopulation.ToList();
Population.Mutate();
Population.ComputeFitness();
generationNumber++;
}
Console.WriteLine($"Generation: {generationNumber}");
watch.Stop();
return(watch.ElapsedMilliseconds);
}
public async Task <IActionResult> PutIndivid(int id, Individ individ)
{
if (id != individ.Id)
{
return(BadRequest());
}
_context.Entry(individ).State = EntityState.Modified;
try
{
await _context.SaveChangesAsync();
}
catch (DbUpdateConcurrencyException)
{
if (!IndividExists(id))
{
return(NotFound());
}
else
{
throw;
}
}
return(NoContent());
}
private Tuple <Individ, Individ> Crossover(Individ pater, Individ mater)
{
var random = new Random();
var child = new Individ();
var antiChild = new Individ();
for (var index = 0; index < pater.Genes.Count; index++)
{
var timeProb = random.NextDouble();
var dayProb = random.NextDouble();
var locationProb = random.NextDouble();
var paterGene = pater.Genes[index];
var materGene = mater.Genes[index];
var childGene = new Gene()
{
Time = timeProb <= CROSSOVER_SELECTION_RATE ? paterGene.Time : materGene.Time,
Day = dayProb <= CROSSOVER_SELECTION_RATE ? paterGene.Day : materGene.Day,
Location = locationProb <= CROSSOVER_SELECTION_RATE ? paterGene.Location : materGene.Location
};
var antiChildGene = new Gene()
{
Time = timeProb <= CROSSOVER_SELECTION_RATE ? materGene.Time : paterGene.Time,
Day = dayProb <= CROSSOVER_SELECTION_RATE ? materGene.Day : paterGene.Day,
Location = locationProb <= CROSSOVER_SELECTION_RATE ? materGene.Location : paterGene.Location
};
child.Genes.Add(childGene);
antiChild.Genes.Add(antiChildGene);
}
return(Tuple.Create(child, antiChild));
}
private void Mutate(Individ individ)
{
var random = new Random();
foreach (var gene in individ.Genes)
{
var timeProb = random.NextDouble();
var dayProb = random.NextDouble();
var locationProb = random.NextDouble();
if (timeProb <= MUTATION_RATE)
{
gene.Time = random.Next(0, AlgorithmData.TimeDecoded.Count);
}
if (dayProb <= MUTATION_RATE)
{
gene.Day = random.Next(0, AlgorithmData.DayDecoded.Count);
}
if (locationProb <= MUTATION_RATE)
{
gene.Location = random.Next(0, AlgorithmData.LocationNumber);
}
}
}
public static void ComputeFitness(this Individ individ)
{
var fitness = 0;
fitness += individ.Genes.Count - individ.Genes.Distinct().Count();
individ.Fitness = fitness;
}
public async Task <IActionResult> Create([Bind("Id,Idanimal,Name,Bio")] Individ individ)
{
if (ModelState.IsValid)
{
_context.Add(individ);
await _context.SaveChangesAsync();
return(RedirectToAction(nameof(Index)));
}
return(View(individ));
}
public Individ GetIndivid(int id, DataBase db, HttpClient client)
{
Individ individ = (Individ)db.SelectQueryTable(id, Constants.Constants.selectIndividQuery);
if (individ == null)
{
System.Threading.Tasks.Task <string> result = client.GetStringAsync(Constants.Constants.individUri + id);
individ = JsonConvert.DeserializeObject <Individ>(result.Result);
db.InsertIntoTable(individ);
}
return(individ);
}
public static bool checkIfAtMostOneLocationIsCapturedPerTurn(Individ _individ)
{
for (int i = 0; i < _individ.Chromosome.Length; i++)
{
var turnsList = _individ.Chromosome[i].Select(x => x.CameraPosition.turn).ToList();
var uniqueTurns = turnsList.Distinct().ToList();
if (turnsList.Count != uniqueTurns.Count)
{
return(false);
}
}
return(true);
}
public static bool checkIfLocationIsInTimeRange(Individ _individ, Inputs _inputs)
{
for (int i = 0; i < _individ.Chromosome.Length; i++)
{
foreach (var item in _individ.Chromosome[i])
{
var collection = _inputs.collections.Single(x => x.Id == item.CollectionID);
if (!collection.isInTimeRange(item.CameraPosition.turn))
{
return(false);
}
}
}
return(true);
}
public void text_jobs_in_stank(Individ A, RichTextBox el)
{
el.Clear();
List <List <int> > job_n_st = raspred_work(A.get_body(), 0);
for (int i = 0; i < job_n_st.Count; i++)
{
List <int> element = job_n_st[i];
el.AppendText("Станок - " + name_of_stank[i] + "\n");
for (int j = 0; j < element.Count; j++)
{
el.AppendText("Работа №" + (j + 1) + " - " + detal_names_time_type_on_id[element[j], 1] + "\n");
}
el.AppendText("Суммарное время работы станка: " + get_time_stank(element) + "\n\n");
}
}//выводит в текстовый блок работы на станках
public long StartAlgorithm(int generations, int sampleSize)
{
bestIndivid = null;
var generationNumber = 0;
var watch = new Stopwatch();
watch.Start();
while (generations != generationNumber && BestFitness() != 0)
{
var newPopulation = new ConcurrentBag <Individ>();
for (var i = 0; i < Population.Individs.Count / 2; i++)
{
var parents = ChoseTwo(sampleSize);
var message = new Message()
{
Command = "childrens",
Individ1 = parents.Item1,
Individ2 = parents.Item2
};
engine.ExecutorService.ScheduleTask(message, result =>
{
newPopulation.Add(result.Individ1);
newPopulation.Add(result.Individ2);
});
}
engine.ExecutorService.WaitToFinish();
var newPopList = newPopulation.ToList();
if (newPopList.Count != 0)
{
Population.Individs = newPopulation.ToList();
}
else
{
}
generationNumber++;
}
var time = watch.ElapsedMilliseconds;
return(time);
}
/* BACK UP Method
*
* public static bool checkCameraOffsetForConsecutivePictures(Individ _individ, Inputs _inputs)
* {
* double w_latitude = 0;
* double w_longitude = 0;
* for (int i = 0; i < _individ.Chromosome.Length; i++)
* {
* var satelliteContent = _individ.Chromosome[i].OrderBy(x => x.CameraPosition.turn).ToList();
* Offset CameraPosition_t0 = new Offset();
* Satellite satellite = _inputs.satellites[i];
*
* // foreach (var item in satelliteContent)
* for (int j = 0; j < satelliteContent.Count; j++)
* {
*
* var item = satelliteContent[j];
*
* if (item.CameraPosition.deltaLat > satellite.D || item.CameraPosition.deltaLong > satellite.D)
* return false;
*
* w_latitude = Math.Abs(item.CameraPosition.deltaLat - CameraPosition_t0.deltaLat) / ((double)item.CameraPosition.turn - (double)CameraPosition_t0.turn);
* w_longitude = Math.Abs(item.CameraPosition.deltaLong - CameraPosition_t0.deltaLong) / ((double)item.CameraPosition.turn - (double)CameraPosition_t0.turn);
*
* if (!(w_latitude <= (double)satellite.W && w_longitude <= (double)satellite.W))
* return false;
*
* CameraPosition_t0 = new Offset();
* CameraPosition_t0.deltaLat = item.CameraPosition.deltaLat;
* CameraPosition_t0.deltaLong = item.CameraPosition.deltaLong;
* CameraPosition_t0.turn = item.CameraPosition.turn;
* }
* }
* return true;
* }
*
*/
//public static bool _checkCameraOffsetForConsecutivePictures(Individ _individ, Inputs _inputs)
//{
// double w_latitude = 0;
// double w_longitude = 0;
// for (int i = 0; i < _individ.Chromosome.Length; i++)
// {
// var satelliteContent = _individ._Chromosome[i].OrderBy(x => x.Key).ToList();
// Offset CameraPosition_t0 = new Offset();
// Satellite satellite = _inputs.satellites[i];
// foreach (var item in satelliteContent)
// {
// if (item.Value.CameraPosition.deltaLat > satellite.D || item.Value.CameraPosition.deltaLong > satellite.D)
// return false;
// w_latitude = Math.Abs(item.Value.CameraPosition.deltaLat - CameraPosition_t0.deltaLat) / ((double)item.Value.CameraPosition.turn - (double)CameraPosition_t0.turn);
// w_longitude = Math.Abs(item.Value.CameraPosition.deltaLong - CameraPosition_t0.deltaLong) / ((double)item.Value.CameraPosition.turn - (double)CameraPosition_t0.turn);
// if (!(w_latitude < satellite.W && w_longitude < satellite.W))
// return false;
// CameraPosition_t0 = new Offset();
// CameraPosition_t0.deltaLat = item.Value.CameraPosition.deltaLat;
// CameraPosition_t0.deltaLong = item.Value.CameraPosition.deltaLong;
// CameraPosition_t0.turn = item.Value.CameraPosition.turn;
// }
// }
// return true;
//}
//public static bool checkCameraOffsetForConsecutivePictures(Individ _individ, Inputs _inputs)
//{
// for (int i = 0; i < _individ.Chromosome.Length; i++)
// {
// foreach (var gene in _individ.Chromosome[i])
// {
// Satellite satellite = _inputs.satellites[i];
// if (gene.CameraPosition.w_lat > satellite.W || gene.CameraPosition.w_long > satellite.W)
// return false;
// }
// }
// return true;
//}
public static bool checkIfOneLocationIsCapturedOnce(Individ _individ)
{
List <int> locationsCaptured = new List <int>();
for (int i = 0; i < _individ.Chromosome.Length; i++)
{
foreach (var location in _individ.Chromosome[i])
{
if (locationsCaptured.Contains(location.LocationID))
{
return(false);
}
locationsCaptured.Add(location.LocationID);
}
}
return(true);
}
public static Individ[] mutate_Population(Individ[] population, Random rand, double chance)
{
//initialize temporary population
Individ[] temp_Population = population;
//Mutate every individual of the population
for (int i = 0; i < temp_Population.Length; i++)
{
for (int j = 0; j < temp_Population[i].genes.Length; j++)
{
if (rand.Next(0, 101) < chance)
{
//random R,G,B,A,X,Y picker
int rand_int = rand.Next(1, 7);
switch (rand_int)
{
case 1:
temp_Population[i].Genes[j].R = rand.Next(0, 256);
break;
case 2:
temp_Population[i].Genes[j].G = rand.Next(0, 256);
break;
case 3:
temp_Population[i].Genes[j].B = rand.Next(0, 256);
break;
case 4:
temp_Population[i].Genes[j].A = rand.Next(0, 256);
break;
case 5:
temp_Population[i].Genes[j].pos[rand.Next(0, 3)].X = rand.Next(0, population[0].source.Width);
break;
case 6:
temp_Population[i].Genes[j].pos[rand.Next(0, 3)].Y = rand.Next(0, population[0].source.Height);
break;
}
}
}
}
return temp_Population;
}
public async Task <ActionResult <Individ> > PostIndivid(Individ individ)
{
_context.Individ.Add(individ);
try
{
await _context.SaveChangesAsync();
}
catch (DbUpdateException)
{
if (IndividExists(individ.Id))
{
return(Conflict());
}
else
{
throw;
}
}
return(CreatedAtAction("GetIndivid", new { id = individ.Id }, individ));
}
private int CaculateFitness(Individ individ)
{
var intersections = new Dictionary <Gene, int>();
foreach (var gene in individ.Genes)
{
if (!intersections.ContainsKey(gene))
{
intersections[gene] = 0;
}
intersections[gene]++;
}
var fitness = 0;
foreach (var keyValuePair in intersections)
{
fitness += keyValuePair.Value - 1;
}
return(fitness);
}
private void btnRunGeneticAlgorithm_Click(object sender, EventArgs e)
{
// Initialize GA
GeneticAlgorithm ga = new GeneticAlgorithm((int)numPopulationSize.Value,
(int)numTournamentSize.Value,
(int)numMaxGenerations.Value,
(int)numTerminationThreshold.Value,
Path.GetFileName(txtPathFile.Text).Split('.')[0],
chbExternalInitialize.Checked);
BestIndivid = ga.RunGeneticAlgorithm(inputs);
// Check Validation of the Best Solution
if (!Validation.checkIfLocationIsInTimeRange(BestIndivid, inputs))
{
MessageBox.Show("The solution is not valid! \n Problem with time range!");
}
if (!Validation.checkCameraOffsetForConsecutivePictures(BestIndivid, inputs)) // This is false..., Why?
{
MessageBox.Show("The solution is not valid! \n Camera offset is greater than w arcseconds between taking two consecutive pictures.");
}
if (!Validation.checkIfOneLocationIsCapturedOnce(BestIndivid))
{
MessageBox.Show("The solution is not valid! \n Location has been captured twice! ");
}
if (!Validation.checkIfAtMostOneLocationIsCapturedPerTurn(BestIndivid))
{
MessageBox.Show("The solution is not valid! \n More than one location has been captured in a turn by the same satellite! ");
}
ExtractSubmissionIntoFile();
MessageBox.Show("Finished! \n Score: " + BestIndivid.Fitness);
}
public static Tuple <Individ, Individ> Crossover(this Individ fatherIndivid, Individ motherIndivid)
{
var brotherIndividGenes = new Gene[AlgorithmData.CoursesNumber * AlgorithmData.GroupsNumber];
var stuckSisterIndividGenes = new Gene[AlgorithmData.CoursesNumber * AlgorithmData.GroupsNumber];
for (var index = 0; index < AlgorithmData.CoursesNumber * AlgorithmData.GroupsNumber; index++)
{
var siblingsGenesTuple = fatherIndivid.Genes[index].Crossover(motherIndivid.Genes[index]);
brotherIndividGenes[index] = siblingsGenesTuple.Item1;
stuckSisterIndividGenes[index] = siblingsGenesTuple.Item2;
}
return(new Tuple <Individ, Individ>
(
new Individ()
{
Genes = brotherIndividGenes.ToList()
},
new Individ()
{
Genes = stuckSisterIndividGenes.ToList()
}
));
}
/*
* Characteristic of Method:
* It recalculates from scratch all the positions of camera per turn between taking two consecutive pictures!
*/
public static bool checkCameraOffsetForConsecutivePictures(Individ _individ, Inputs _inputs)
{
double w_latitude = 0;
double w_longitude = 0;
for (int i = 0; i < _individ.Chromosome.Length; i++)
{
var satelliteContent = _individ.Chromosome[i].OrderBy(x => x.Turn).ToList();
Offset CameraPosition_t0 = new Offset();
Satellite satellite = _inputs.satellites[i];
// foreach (var item in satelliteContent)
for (int j = 0; j < satelliteContent.Count; j++)
{
var item = satelliteContent[j];
if (item.CameraPosition.deltaLat > satellite.D || item.CameraPosition.deltaLong > satellite.D)
{
return(false);
}
w_latitude = Math.Abs(item.CameraPosition.deltaLat - CameraPosition_t0.deltaLat) / ((double)item.CameraPosition.turn - (double)CameraPosition_t0.turn);
w_longitude = Math.Abs(item.CameraPosition.deltaLong - CameraPosition_t0.deltaLong) / ((double)item.CameraPosition.turn - (double)CameraPosition_t0.turn);
if (w_latitude > (double)satellite.W && w_longitude > (double)satellite.W)
{
return(false);
}
CameraPosition_t0 = new Offset();
CameraPosition_t0.deltaLat = item.CameraPosition.deltaLat;
CameraPosition_t0.deltaLong = item.CameraPosition.deltaLong;
CameraPosition_t0.turn = item.CameraPosition.turn;
}
}
return(true);
}
public int BestFitness()
{
var bestFitnessPop = Int32.MaxValue;
Individ bestIndividPop = null;
Population.Individs.ForEach(individ =>
{
if (bestFitnessPop > individ.Fitness)
{
bestFitnessPop = individ.Fitness;
bestIndividPop = individ;
}
});
if (bestIndivid == null)
{
bestIndivid = bestIndividPop;
}
else if (bestIndividPop != null && bestIndivid.Fitness > bestIndividPop.Fitness)
{
bestIndivid = bestIndividPop;
}
return(bestFitnessPop);
}
public static void Mutate(this Individ individ)
{
individ.Genes.AsParallel().ForAll(gene => gene.Mutate());
}
private void button1_Click(object sender, EventArgs e)
{
Application.DoEvents();
//initialize source image
Source_Image_Path.ShowDialog();
Bitmap source_Image = (Bitmap)Image.FromFile(Source_Image_Path.FileName);
Source_Imagebox.BackgroundImage = source_Image;
Application.DoEvents();
//initialize Population
int numGenes = 10;
int popSize = 32;
int mutateChance = 5;
Random rand = new Random();
Individ[] population = new Individ[popSize];
for (int i = 0; i < popSize; i++)
{
population[i] = new Individ(source_Image, numGenes, rand);
}
//Sorting initial Population
Array.Sort(population, delegate (Individ num1, Individ num2)
{
return num1.fitness.CompareTo(num2.fitness);
});
//Evolving population until best individ fitness meets some value 5500000
while(population[0].fitness > 55000)
{
//evolving Population
population = mate(population, rand, 4);
//Mutate population
population = mutate_Population(population, rand, mutateChance);
//Sorting Population
Array.Sort(population, delegate (Individ num1, Individ num2)
{
return num1.fitness.CompareTo(num2.fitness);
});
//print best image of the generation
Application.DoEvents();
Genes_Textbox.Text = (population[0].fitness + Environment.NewLine) + Genes_Textbox.Text;
Evo_Imagebox.BackgroundImage = population[0].evoImage;
Application.DoEvents();
}
Application.DoEvents();
Genes_Textbox.Text = (population[0].fitness + Environment.NewLine) + Genes_Textbox.Text;
Evo_Imagebox.BackgroundImage = population[0].evoImage;
Application.DoEvents();
}
public static Individ procreation(Individ Parent1, Individ Parent2, Random rand)
{
//initialize a cutoff point where all the genes of parent 1 will be transferred from before the point
//and all the genes from parent 2 will be transferred to the kid from after the point
int cutoff = rand.Next(0, Parent1.genes.Length);
//Initialize kid
Individ kid = new Individ(Parent1.source, Parent1.genes.Length, rand);
Triangle[] kid_Genes = new Triangle[kid.genes.Length];
for (int i = 0; i < kid.genes.Length; i++)
{
if (i < cutoff)
{
kid_Genes[i] = Parent1.genes[i];
}
else kid_Genes[i] = Parent2.genes[i];
}
kid.Genes = kid_Genes;
return kid;
}
}// создает новую популяцию из текущей
private Individ[] crossengover(Individ A1, Individ A2)
{
List <List <int> > body_1 = new List <List <int> >(A1.get_body()),
body_2 = new List <List <int> >(A2.get_body()),
body_3 = new List <List <int> >(),
body_4 = new List <List <int> >();
Individ[] result = new Individ[2];
for (int ID_yach = 0; ID_yach < body_1.Count; ID_yach++)
{
List <int> yach_1 = body_1[ID_yach],
yach_2 = body_2[ID_yach],
yach_3 = new List <int>(),
yach_4 = new List <int>();
List <int[]> col_n_types_1 = get_col_n_types_jobs(yach_1);
List <int[]> col_n_types_2 = get_col_n_types_jobs(yach_2);
//порядок вперед для 1 ребенка
for (int id_job = 0; id_job < yach_1.Count; id_job++)
{
for (int i = 0; i < col_n_types_1.Count; i++)
{
int[] elem = col_n_types_1[i];
if (elem[0] == yach_1[id_job])
{
if (elem[1] != 0)
{
elem[1]--;
yach_3.Add(yach_1[id_job]);
col_n_types_1[i] = elem;
break;
}
}
}
for (int i = 0; i < col_n_types_1.Count; i++)
{
int[] elem = col_n_types_1[i];
if (elem[0] == yach_2[id_job])
{
if (elem[1] != 0)
{
elem[1]--;
yach_3.Add(yach_2[id_job]);
break;
}
}
}
}
for (int i = 0; i < col_n_types_1.Count; i++)
{
int[] elem = col_n_types_1[i];
for (int j = 0; j < elem[1]; j++)
{
yach_3.Add(elem[0]);
}
}
// обратный порядок для 2 ребенка
for (int id_job = yach_1.Count - 1; id_job >= 0; id_job--)
{
//MessageBox.Show(yach_1[id_job] + "");
for (int i = 0; i < col_n_types_2.Count; i++)
{
int[] elem = col_n_types_2[i];
if (elem[0] == yach_1[id_job])
{
if (elem[1] != 0)
{
elem[1]--;
yach_4.Add(yach_1[id_job]);
col_n_types_2[i] = elem;
break;
}
}
}
for (int i = 0; i < col_n_types_2.Count; i++)
{
int[] elem = col_n_types_2[i];
if (elem[0] == yach_2[id_job])
{
if (elem[1] != 0)
{
elem[1]--;
yach_4.Add(yach_2[id_job]);
break;
}
}
}
}
for (int i = 0; i < col_n_types_2.Count; i++)
{
int[] elem = col_n_types_2[i];
for (int j = 0; j < elem[1]; j++)
{
yach_4.Add(elem[0]);
}
}
//MessageBox.Show(yach_4.Count +"");
body_3.Add(yach_3);
body_4.Add(yach_4);
/*string red = "";
* foreach (int[] el in col_n_types)
* {
* red += el[0] + " " + el[1] + "\n";
* }
* MessageBox.Show(red);*/
}
result[0] = new Individ(body_3, false);
get_Function(result[0].get_body());
result[1] = new Individ(body_4, false);
get_Function(result[1].get_body());
return(result);
}// скрещивание двух особей
private List <Individ> selection_individ()
{
Individ[] cross = new Individ[2];
List <Individ> result = new List <Individ>();
List <Individ> VERH = new List <Individ>();
List <Individ> NIZ = new List <Individ>();
int col_VERH = Convert.ToInt32(col_population * _PERSENTV_), col_NIZ = Convert.ToInt32(col_population * _PERSENTN_);
for (int i = 0; i < col_VERH; i++)
{
VERH.Add(NOW_POPULATION[i]);
}
for (int i = (NOW_POPULATION.Count - 1); i >= NOW_POPULATION.Count - col_NIZ; i--)
{
NIZ.Add(NOW_POPULATION[i]);
}
result.Add(VERH[0]);
for (int i = 0; i < VERH.Count - 1; i++)
{
for (int j = i + 1; j < VERH.Count; j++)
{
cross = crossengover(VERH[i], VERH[j]);
result.Add(cross[0]);
result.Add(cross[1]);
}
//MessageBox.Show("r1=" + get_Function(VERH[0].get_body()) + " r2=" + get_Function(VERH[1].get_body()) + "\n ch1=" + get_Function(result[0].get_body()) + " ch2=" + get_Function(result[1].get_body()));
}
for (int i = 0; i < NIZ.Count - 1; i++)
{
for (int j = i + 1; j < NIZ.Count; j++)
{
cross = crossengover(NIZ[i], NIZ[j]);
result.Add(cross[0]);
result.Add(cross[1]);
}
//MessageBox.Show("r1=" + get_Function(VERH[0].get_body()) + " r2=" + get_Function(VERH[1].get_body()) + "\n ch1=" + get_Function(result[0].get_body()) + " ch2=" + get_Function(result[1].get_body()));
}
for (int i = 1; i < VERH.Count; i++)
{
if (result.Count >= col_population)
{
break;
}
result.Add(VERH[i]);
}
for (int i = 0; i < NIZ.Count; i++)
{
if (result.Count >= col_population)
{
break;
}
result.Add(NIZ[i]);
}
if (result.Count > col_population)
{
int col_del = result.Count - col_population;
for (int i = result.Count - 1; i >= col_population; i--)
{
result.RemoveAt(i);
}
}
//MessageBox.Show(result.Count + "");
NOW_POPULATION = result;
Pver_n_sort();
return(result);
}// создает новую популяцию из текущей
public IndividInfo(Individ individ, IndividImages images)
{
this.individ = individ;
this.images = images;
}
public MutationResponse()
{
individ = new Individ();
}
