diff --git a/src/local_search.py b/src/local_search.py
index 8377654..2b5d7fa 100644
--- a/src/local_search.py
+++ b/src/local_search.py
@@ -3,14 +3,17 @@ from numpy.random import choice, seed
 
 def get_first_random_solution(m, data):
     seed(42)
-    random_indexes = choice(len(data.index), size=m)
-    return data.iloc[random_indexes]
+    random_indexes = choice(len(data.index), size=m, replace=False)
+    return data.loc[random_indexes]
 
 
 def replace_worst_element(previous, data):
     solution = previous.copy()
     worst_index = solution["distance"].astype(float).idxmin()
-    solution.loc[worst_index] = data.sample(random_state=42).squeeze()
+    random_element = data.sample().squeeze()
+    while solution.isin(random_element.values.ravel()).any().any():
+        random_element = data.sample().squeeze()
+    solution.loc[worst_index] = random_element
     return solution, worst_index
 
 
@@ -28,11 +31,6 @@ def get_random_solution(previous, data):
     return solution
 
 
-def remove_duplicates(element, data):
-    duplicate_free_df = data.query(
-        "(source not in @element.source) or (destination not in @element.destination)"
-    )
-    return duplicate_free_df
 
 
 def explore_neighbourhood(element, data, max_iterations=100000):
@@ -41,7 +39,6 @@ def explore_neighbourhood(element, data, max_iterations=100000):
     for _ in range(max_iterations):
         previous_solution = neighbourhood[-1]
         neighbour = get_random_solution(previous=previous_solution, data=data)
-        data = remove_duplicates(element=neighbour, data=data)
         if neighbour.equals(previous_solution):
             break
         neighbourhood.append(neighbour)