diff --git a/src/genetic_algorithm.py b/src/genetic_algorithm.py
index 54a1b03..73556ef 100644
--- a/src/genetic_algorithm.py
+++ b/src/genetic_algorithm.py
@@ -59,12 +59,14 @@ def select_distinct_genes(matching_genes, parents, m):
     return first_parent_genes, second_parent_genes
 
 
-def select_random_genes(matching_genes, parents, m):
-    random_parent = parents[randint(len(parents))]
-    distinct_indexes = delete(arange(m), matching_genes)
-    genes = random_parent.point.iloc[distinct_indexes].values
-    shuffle(genes)
-    return genes
+def select_random_genes(matching_genes, parents):
+    first_parent = parents[0].query("point not in @matching_genes")
+    second_parent = parents[1].query("point not in @matching_genes")
+    first_genes = first_parent.point.values
+    second_genes = second_parent.point.values
+    shuffle(first_genes)
+    shuffle(second_genes)
+    return first_genes, second_genes
 
 
 def select_random_parent(parents):
@@ -110,7 +112,6 @@ def populate_offspring(values):
         offspring = offspring.append(aux)
     offspring["distance"] = 0
     offspring["fitness"] = 0
-    offspring = offspring[1:]
     return offspring
 
 
@@ -122,24 +123,26 @@ def uniform_crossover(parents, m):
     return viable_offspring
 
 
-def position_crossover(parents, m):
+def position_crossover(parents):
     matching_genes = get_matching_genes(parents)
-    shuffled_genes = select_random_genes(matching_genes, parents, m)
-    first_offspring = populate_offspring(values=[matching_genes, shuffled_genes])
-    second_offspring = populate_offspring(values=[matching_genes, shuffled_genes])
-    return [first_offspring, second_offspring]
+    first_genes, second_genes = select_random_genes(matching_genes, parents)
+    first_offspring = populate_offspring(values=[matching_genes, first_genes])
+    second_offspring = populate_offspring(values=[matching_genes, second_genes])
+    return first_offspring, second_offspring
 
 
 def crossover(mode, parents, m):
     split_parents = list(zip(*[iter(parents)] * 2))
     offspring = []
     if mode == "uniform":
-        for i in range(len(split_parents)):
-            offspring.append(uniform_crossover(split_parents[i], m))
-            offspring.append(uniform_crossover(split_parents[i], m))
+        for element in split_parents:
+            offspring.append(uniform_crossover(element, m))
+            offspring.append(uniform_crossover(element, m))
     else:
-        crossover_func = partial(position_crossover, m=m)
-        offspring = [*map(crossover_func, split_parents)]
+        for element in split_parents:
+            first_offspring, second_offspring = position_crossover(element)
+            offspring.append(first_offspring)
+            offspring.append(second_offspring)
     return offspring