diff --git a/lib/ultra_mastermind_obj.py b/lib/ultra_mastermind_obj.py
index 796c240..d54f359 100644
--- a/lib/ultra_mastermind_obj.py
+++ b/lib/ultra_mastermind_obj.py
@@ -1,21 +1,85 @@
 # Librairie du projet en version orientée objet
 
+import random
+
+def min_i(array: list[int]) -> int:
+	min_val = array[0]
+	min_i = 0
+	for i in range(len(array)):
+		if array[i] < min_val:
+			min_val = array[i]
+			min_i = i 
+	return min_i
+
+def max_i(array: list[int]) -> int:
+	max_val = array[0]
+	max_i = 0
+	for i in range(len(array)):
+		if array[i] > max_val:
+			max_val = array[i]
+			max_i = i 
+	return max_i
+
 class Population:
 	"""
 	Classe qui représente notre population d'individuts
 	"""
-	def __init__(self, ng, l, n, ts, pm, tm):
-		self.individuals = [Individual().randomize(l) for _ in range(n)]
+	def __init__(self, pm, ng, n, ts, tm):
+		self.individuals = [Individual() for _ in range(n)]
+		for individual in self.individuals: 
+			individual.randomize(len(pm))
+		self.pm = pm
 		self.ng = ng
-		self.l = l
+		self.l = len(pm)
 		self.n = n
 		self.ts = ts
-		self.pm = pm
 		self.tm = tm
 
 	def select(self) -> None:
-		# TODO
-		pass
+		fitness_list = []
+		for individual in self.individuals:
+			fitness_list.append(individual.fitness(self.pm))
+		for i in range(int(1 - (self.ts * self.l))):
+			least = min_i(self.individuals)
+			fitness.pop(least)
+			self.individuals.pop(least)
+
+	def reproduct(self) -> None:
+		new = []
+		while len(self.individuals) != self.n:
+			cut = random.randint(int(self.l / 3), int(2 * self.l / 3))
+			indivi_1 = self.individuals[random.randint(0, len(self.individuals) - 1)]
+			indivi_2 = self.individuals[random.randint(0, len(self.individuals) - 1)]
+			while indivi_1 == indivi_2:
+				indivi_2 = self.individuals[random.randint(0, len(self.individuals) - 1)]
+			new_chromozome = indivi_1.getChromozome()[:cut] + indivi_2.getChromozome()[cut:]
+			new.append(Individual.setChromozome(new_chromozome))
+		self.individuals += new
+
+	def mutate(self) -> None:
+		mutated = []
+		for i in range(int(self.tm * self.n)):
+			to_mutate = self.individuals[random.randint(0, self.n - 1)]
+			while to_mutate in mutated:
+				to_mutate = self.individuals[random.randint(0, self.n - 1)]
+			to_mutate.mutate()
+			mutated.append(to_mutate)
+
+	def print_best(self) -> None:
+		fitness_list = []
+		for individual in self.individuals:
+			fitness_list.append(individual.fitness(self.pm))
+		print(self.individuals[max_i(fitness_list)].getChromozome)
+
+	def run(self) -> None:
+		for i in range(self.ng):
+			print("select")
+			self.select()
+			print("reproduct")
+			self.reproduct()
+			print("mutate")
+			self.mutate()
+			self.print_best()
 
 class Individual:
 	"""
@@ -26,15 +90,24 @@ class Individual:
 
 	def setChromozome(self, c: str) -> None:
 		self.chromozome = c
+	
+	def getChromozome(self) -> str:
+		return self.chromozome
 
-	def randomize(self, l: int) -> None:
-		# TODO
-		pass
+	def randomize(self, l) -> None:
+		new = ""
+		for i in range(l):
+			new += chr(random.randint(0, 255))
+		self.chromozome = new
 
-	def fitness(self, pm: str) -> float:
-		# TODO
-		pass
+	def fitness(self, pm) -> float:
+		sum = 0
+		for i in range(len(self.chromozome)):
+			sum += abs(ord(self.chromozome[i]) - ord(pm[i]))
+		return -sum
+
+	def mutate(self) -> None:
+		new = list(len(self.chromozome))
+		new[random.randint(0, len(self.chromozome))] = chr(random.randint(0, 255))
+		self.chromozome = "".join(new)
 
-	def mutate(self, tm: float) -> None:
-		# TODO
-		pass
diff --git a/main.py b/main.py
index 3749468..ce2dcde 100644
--- a/main.py
+++ b/main.py
@@ -1,11 +1,13 @@
 # fichier d'exemple 'run' du projet
 
 # project libs importations
-import lib.ultra_mastermind_obj
-import lib.ultra_mastermind_imp
+import lib.ultra_mastermind_obj as libobj
+import lib.ultra_mastermind_imp as libomp
 
 def main() -> None:
-	pass
+    pop = libobj.Population('saucisse', 1000, 100, 0.3, 0.3)
+    pop.run()
 
 if __name__ == "__main__":
 	main()
+