diff --git a/src/initialization/population_structure/population.py b/src/initialization/population_structure/population.py
index 98f5518..435af04 100644
--- a/src/initialization/population_structure/population.py
+++ b/src/initialization/population_structure/population.py
@@ -8,6 +8,10 @@ class Population:
         self.fitness = None
         self.mating_pool = []
 
+    def size(self):
+        """Returns the size of the population"""
+        return len(self.chromosome_list)
+
     def get_closet_fitness(self,value):
         """Get the chomosome that has the closets fitness to the value defined"""
         pass
diff --git a/src/mutation/mutation_methods.py b/src/mutation/mutation_methods.py
index 7515b4d..e1e3166 100644
--- a/src/mutation/mutation_methods.py
+++ b/src/mutation/mutation_methods.py
@@ -44,5 +44,3 @@ class Mutation_Methods:
             gene_mutate_count = int(gene_mutate_count_static)
 
         return chromosome_set
-
-        
diff --git a/src/survivor_selection/survivor_selection_methods.py b/src/survivor_selection/survivor_selection_methods.py
index 530ffd8..99e8daa 100644
--- a/src/survivor_selection/survivor_selection_methods.py
+++ b/src/survivor_selection/survivor_selection_methods.py
@@ -7,15 +7,6 @@ from initialization.chromosome_structure.chromosome import Chromosome
 class Survivor_Selection:
     """Survivor selection determines which individuals should be brought to the next generation"""
 
-    def remove_worst(ga, next_population):
-        """
-        Will bring all but the worst-performing chromosomes from the current generation.
-        The exact number of chromosomes removed depends on how many offspring were generated by parent selection.
-        """
-        iterator = 0
-        # While the size of the next population is less than it should be (as determined by the user)
-        while len(next_population.get_all_chromosomes()) < ga.population_size:
-            # Add the best chromosome from the current population that hasn't already been brought over
-            next_population.add_chromosome(ga.population.get_all_chromosomes()[iterator])
-            iterator += 1
-        return next_population
\ No newline at end of file
+    def fill_in_best(ga, next_population):
+        """Fills in the next population with the best chromosomes from the last population until the population size is met."""
+        return ga.population[:ga.population_size-next_population.size()] + next_population