public static void Update_Generation(aCitizen New_Citizen) {
int Max_Index = Heap_Max.Find_First_Best();
if (New_Citizen.nAttacks < Citizen[Max_Index].nAttacks) {
Heap_Min.Pop(Heap_Min.pos[Max_Index]);
Heap_Max.Pop(Heap_Max.pos[Max_Index]);
Citizen[Max_Index].Assign(New_Citizen);
Heap_Min.Push(Citizen[Max_Index].nAttacks, Max_Index);
Heap_Max.Push(Citizen[Max_Index].nAttacks, Max_Index);
}
}
public static void Init() {
Citizen = new aCitizen[Population];
for (int i = 0; i < Population; i++) {
Citizen[i] = new aCitizen(N);
Citizen[i].Randomize();
Citizen[i].Local_Optimization();
}
Heap_Min = new Heap(Population, true);
Heap_Max = new Heap(Population, false);
for (int i = 0; i < Population; i++) {
Heap_Min.Push(Citizen[i].nAttacks, i);
Heap_Max.Push(Citizen[i].nAttacks, i);
}
}
public static void Genetic_Algorithm() {
int nGenerations = 0;
result = new aCitizen(N);
while (true) {
nGenerations++;
System.out.println("\nGeneration " + nGenerations);
int index1 = Heap_Min.Find_First_Best();
System.out.println("Minimum of attacking: " + Citizen[index1].nAttacks);
if (Citizen[index1].nAttacks == 0) {
found = true;
result = Citizen[index1];
break;
}
int index2 = Heap_Min.Find_Second_Best();
Update_Generation(index1, index2);
while (true) {
index1 = Random_Int(Population);
index2 = Random_Int(Population);
if (index1 != index2) break;
}
Update_Generation(index1, index2);
index1 = Heap_Min.Find_First_Best();
index2 = Heap_Max.Find_Second_Best();
Update_Generation(index1, index2);
if (nGenerations == Max_nGenerations) break;
}
result = Citizen[Heap_Min.Find_First_Best()];
}
