diff --git a/src/genetic_algorithm.py b/src/genetic_algorithm.py
index 7561fb5..91d9136 100644
--- a/src/genetic_algorithm.py
+++ b/src/genetic_algorithm.py
@@ -1,4 +1,4 @@
-from numpy import sum, append, intersect1d
+from numpy import sum, append, intersect1d, array_equal
 from numpy.random import randint, choice, shuffle
 from pandas import DataFrame
 from math import ceil
@@ -133,15 +133,28 @@ def position_crossover(parents):
     return first_offspring, second_offspring
 
 
+def group_parents(parents):
+    parent_pairs = []
+    for i in range(0, len(parents), 2):
+        first = parents[i]
+        second = parents[i + 1]
+        if array_equal(first.point.values, second.point.values):
+            tmp = second
+            second = parents[i - 2]
+            parents[i - 2] = tmp
+        parent_pairs.append([first, second])
+    return parent_pairs
+
+
 def crossover(mode, parents, m):
-    split_parents = list(zip(*[iter(parents)] * 2))
+    parent_groups = group_parents(parents)
     offspring = []
     if mode == "uniform":
-        for element in split_parents:
+        for element in parent_groups:
             offspring.append(uniform_crossover(element, m))
             offspring.append(uniform_crossover(element, m))
     else:
-        for element in split_parents:
+        for element in parent_groups:
             first_offspring, second_offspring = position_crossover(element)
             offspring.append(first_offspring)
             offspring.append(second_offspring)
@@ -194,7 +207,7 @@ def tournament_selection(population):
 
 def check_element_population(element, population):
     for item in population:
-        if all(element.point.values) == all(item.point.values):
+        if array_equal(element.point.values, item.point.values):
             return True
     return False