diff --git a/genetic_algorithm/genetic_algorithm.py b/genetic_algorithm/genetic_algorithm.py
index 0c2e2ef..38e0e40 100644
--- a/genetic_algorithm/genetic_algorithm.py
+++ b/genetic_algorithm/genetic_algorithm.py
@@ -6,7 +6,10 @@ from fastapi import FastAPI, HTTPException, Request
 
 from schemas import TripRequest
 
-def load_graph_from_request(request: TripRequest) -> Tuple[Dict[Tuple[str, str], List[Any]], Dict[Tuple[str, str], List[Any]], str, str, List[Dict], List[Dict], datetime, datetime]:
+
+def load_graph_from_request(request: TripRequest) -> Tuple[
+    Dict[Tuple[str, str], List[Any]], Dict[Tuple[str, str], List[Any]], str, str, List[Dict], List[
+        Dict], datetime, datetime]:
     graphTo = {}
     flightsDataTo = []
     graphBack = {}
@@ -71,7 +74,10 @@ def load_graph_from_request(request: TripRequest) -> Tuple[Dict[Tuple[str, str],
     return graphTo, graphBack, start_point, end_point, flightsDataTo, flightsDataBack, departure_date, departure_date_return
 
 
-def path_length_and_time(path, graph):
+def path_length_and_time(path, graph, start_point, end_point, departure_date):
+    if path[0] != start_point or path[-1] != end_point:
+        return float('inf'), None, None
+
     length = 0
     if (path[0], path[1]) not in graph:
         return float('inf'), None, None
@@ -79,6 +85,9 @@ def path_length_and_time(path, graph):
     start_time = graph[(path[0], path[1])][0][1]
     end_time = start_time
 
+    if start_time.date() != departure_date:
+        return float('inf'), start_time, end_time
+
     for i in range(len(path) - 1):
         if (path[i], path[i + 1]) not in graph:
             return float('inf'), start_time, end_time
@@ -91,7 +100,7 @@ def path_length_and_time(path, graph):
     return length, start_time, end_time
 
 
-def generate_population(size, start, end, graph, max_attempts=100):
+def generate_population(size, start, end, graph, departure_date, max_attempts=100):
     population = []
     nodes = list(set([k[0] for k in graph.keys()] + [k[1] for k in graph.keys()]))
     for i in range(size):
@@ -111,15 +120,20 @@ def generate_population(size, start, end, graph, max_attempts=100):
                 if len(path) > len(nodes):
                     break
             if path[-1] == end:
-                population.append(path)
+                # Проверка даты вылета первого рейса
+                first_leg = (path[0], path[1])
+                if first_leg in graph and graph[first_leg][0][1].date() == departure_date:
+                    population.append(path)
                 break
             attempts += 1
     return population
 
 
-def select_parents(population, graph):
-    sorted_population = sorted(population, key=lambda p: path_length_and_time(p, graph)[0])
-    valid_parents = [p for p in sorted_population if path_length_and_time(p, graph)[0] != float('inf')]
+def select_parents(population, graph, start_point, end_point, departure_date):
+    sorted_population = sorted(population,
+                               key=lambda p: path_length_and_time(p, graph, start_point, end_point, departure_date)[0])
+    valid_parents = [p for p in sorted_population if
+                     path_length_and_time(p, graph, start_point, end_point, departure_date)[0] != float('inf')]
     return valid_parents[:len(valid_parents) // 2]
 
 
@@ -141,8 +155,8 @@ def mutate(child):
     return child
 
 
-def update_best_paths(best_paths, path, graph, max_best_paths=10):
-    length, _, _ = path_length_and_time(path, graph)
+def update_best_paths(best_paths, path, graph, start_point, end_point, departure_date, max_best_paths=10):
+    length, _, _ = path_length_and_time(path, graph, start_point, end_point, departure_date)
     if path not in best_paths:
         best_paths[path] = length
     if len(best_paths) > max_best_paths:
@@ -151,10 +165,10 @@ def update_best_paths(best_paths, path, graph, max_best_paths=10):
 
 
 def genetic_algorithm(start, end, graph, flights_data, type, departure_date, population_size=2000, generations=100):
-    population = generate_population(population_size, start, end, graph)
+    population = generate_population(population_size, start, end, graph, departure_date)
     best_paths = {}  # Словарь для хранения уникальных лучших маршрутов и их длин
     for generation in range(generations):
-        parents = select_parents(population, graph)
+        parents = select_parents(population, graph, start, end, departure_date)
 
         # Если не удалось выбрать родителей, завершить алгоритм
         if not parents:
@@ -169,7 +183,7 @@ def genetic_algorithm(start, end, graph, flights_data, type, departure_date, pop
                 child = mutate(child)
             if child[-1] == end:
                 new_population.append(child)
-                update_best_paths(best_paths, tuple(child), graph)
+                update_best_paths(best_paths, tuple(child), graph, start, end, departure_date)
         population = new_population
 
     best_paths = sorted(best_paths.items(), key=lambda item: item[1])
@@ -187,8 +201,12 @@ def genetic_algorithm(start, end, graph, flights_data, type, departure_date, pop
                         "destinationPoint": flight['destinationPoint']
                     })
                     break
-        result.append({
-            type: path_data,
-        })
 
-    return result
+        # Финальная проверка пути
+        if path[0] == start and path[-1] == end and path_length_and_time(path, graph, start, end, departure_date)[
+            0] != float('inf'):
+            result.append({
+                type: path_data,
+            })
+
+    return result
\ No newline at end of file