static void Main(string[] args)
{
//init
int population = Global.population();
int b = Global.b();
// Set in Global
int[] X = Global.Xvalue();
int[] Y = Global.Yvalue();
int[] Z = Global.Zvalue();
Multiset initialSet = Global.Initial();
//Random
Multiset possibleRandom = Global.GenerateRandom(100);
Console.Write("\n Here is a possible random solution that is solveable");
possibleRandom.print();
Boolean isSolveable = initialSet.CheckSolvability(b);
if (isSolveable)
{
//Randomly create population parents
List <Multiset> parentList = new List <Multiset>();
for (int i = 0; i < population; i++)
{
Multiset holder = new Multiset(Global.Xvalue(), Global.Yvalue(), Global.Zvalue());
holder = Multiset.Randomize();
parentList.Add(holder);
}
List <Multiset> NextGen = parentList;
for (int i = 0; i < Global.Generations(); i++)
{
Console.Write("Finding Generation {0}\n", i + 1);
NextGen = FindNextGen(NextGen);
Console.Write("Generation {0}'s best score is {1}\n", i + 1, NextGen[0].totalScore);
Console.Write("Gen {0}'s Solution: \n", i + 1);
NextGen[0].print();
Console.Write("\n");
}
List <Node> guess = WoC(NextGen);
Multiset finalguess = Node.FindBest(guess);
Console.Write("Best guess's score is {0}\n", finalguess.totalScore);
Console.Write("Final Guess Solution: \n");
Node.print(finalguess.ToNodeList());
Console.WriteLine("Hello World!");
Console.ReadKey(true);
}
}
public static List <Multiset> FindNextGen(List <Multiset> parentList)
{
//Creates (parentList.Count/2) Children
int totalCount = 0; //keeps track of the amount of children in the NextGen List.
List <Multiset> NextGen = new List <Multiset>();
for (int k = 0; k < parentList.Count; k += 2)
{
Multiset holder = new Multiset(Global.Xvalue(), Global.Yvalue(), Global.Zvalue());
holder = Multiset.CreateChild(parentList[k], parentList[k + 1]);
NextGen.Add(holder);
totalCount++;
}
//Sort parentList by ascending totalScore, then add the top 10% to NextGen.
parentList.Sort((x, y) => x.totalScore.CompareTo(y.totalScore));
//Add the top 10% of parents into the NextGen population
for (int r = 0; r < parentList.Count / 10; r++)
{
//parentList[r].print();
NextGen.Add(parentList[r]);
totalCount++;
}
//Creates the last 10% of the NextGen children by crossover of the top 80% parents
//Check top 20% parent size. -> Console.WriteLine("Top 20% parents size should be 240= {0}",parentList.Count*(.8));
for (int s = 0; s < parentList.Count * (0.2); s += 2)
{
Multiset holder = new Multiset(Global.Xvalue(), Global.Yvalue(), Global.Zvalue());
holder = Multiset.CreateChild(parentList[s + 1], parentList[s]);
NextGen.Add(holder);
totalCount++;
}
//Mutator Function
Random randMutate = new Random();
parentList.Sort((x, y) => x.totalScore.CompareTo(y.totalScore));
for (int v = 0; v < parentList.Count * .3; v++)
{
Multiset holder = new Multiset(Global.Xvalue(), Global.Yvalue(), Global.Zvalue());
holder = Multiset.CreateChild(Multiset.Randomize(), parentList[v], 1);
NextGen.Add(holder);
}
//int increment = 1;
//int counter = 0;
int startPercentage = 1;
NextGen.Sort((x, y) => x.totalScore.CompareTo(y.totalScore));
for (int v = 0; v < NextGen.Count; v++)
{
if (v > ((NextGen.Count * (0.01)) * startPercentage))
{
startPercentage++;
}
int r = randMutate.Next(startPercentage, 101);
if (r == startPercentage)
{
//Mutate child
NextGen[v] = NextGen[v].MutateChild();
}
//increment++;
}
return(NextGen);
//end
}
