diff --git a/eoh/src/eoh/methods/ael/ael.py b/eoh/src/eoh/methods/ael/ael.py
index e3edc780..d2ea8f0f 100644
--- a/eoh/src/eoh/methods/ael/ael.py
+++ b/eoh/src/eoh/methods/ael/ael.py
@@ -135,21 +135,21 @@ def run(self):
                 op_w = self.operator_weights[i]
                 if (np.random.rand() < op_w):
                     parents, offsprings = interface_ec.get_algorithm(population, op)
-                self.add2pop(population, offsprings)  # Check duplication, and add the new offspring
-                for off in offsprings:
-                    print(" Obj: ", off['objective'], end="|")
-                # if is_add:
-                #     data = {}
-                #     for i in range(len(parents)):
-                #         data[f"parent{i + 1}"] = parents[i]
-                #     data["offspring"] = offspring
-                #     with open(self.output_path + "/results/history/pop_" + str(pop + 1) + "_" + str(
-                #             na) + "_" + op + ".json", "w") as file:
-                #         json.dump(data, file, indent=5)
-                # populatin management
-                size_act = min(len(population), self.pop_size)
-                population = self.manage.population_management(population, size_act)
-                print()
+                    self.add2pop(population, offsprings)  # Check duplication, and add the new offspring
+                    for off in offsprings:
+                        print(" Obj: ", off['objective'], end="|")
+                    # if is_add:
+                    #     data = {}
+                    #     for i in range(len(parents)):
+                    #         data[f"parent{i + 1}"] = parents[i]
+                    #     data["offspring"] = offspring
+                    #     with open(self.output_path + "/results/history/pop_" + str(pop + 1) + "_" + str(
+                    #             na) + "_" + op + ".json", "w") as file:
+                    #         json.dump(data, file, indent=5)
+                    # populatin management
+                    size_act = min(len(population), self.pop_size)
+                    population = self.manage.population_management(population, size_act)
+                    print()
 
 
             # Save population to a file
@@ -168,4 +168,3 @@ def run(self):
             for i in range(len(population)):
                 print(str(population[i]['objective']) + " ", end="")
             print()
-
diff --git a/eoh/src/eoh/methods/eoh/eoh.py b/eoh/src/eoh/methods/eoh/eoh.py
index e160b7d2..16030f8e 100644
--- a/eoh/src/eoh/methods/eoh/eoh.py
+++ b/eoh/src/eoh/methods/eoh/eoh.py
@@ -149,21 +149,21 @@ def run(self):
                 op_w = self.operator_weights[i]
                 if (np.random.rand() < op_w):
                     parents, offsprings = interface_ec.get_algorithm(population, op)
-                self.add2pop(population, offsprings)  # Check duplication, and add the new offspring
-                for off in offsprings:
-                    print(" Obj: ", off['objective'], end="|")
-                # if is_add:
-                #     data = {}
-                #     for i in range(len(parents)):
-                #         data[f"parent{i + 1}"] = parents[i]
-                #     data["offspring"] = offspring
-                #     with open(self.output_path + "/results/history/pop_" + str(pop + 1) + "_" + str(
-                #             na) + "_" + op + ".json", "w") as file:
-                #         json.dump(data, file, indent=5)
-                # populatin management
-                size_act = min(len(population), self.pop_size)
-                population = self.manage.population_management(population, size_act)
-                print()
+                    self.add2pop(population, offsprings)  # Check duplication, and add the new offspring
+                    for off in offsprings:
+                        print(" Obj: ", off['objective'], end="|")
+                    # if is_add:
+                    #     data = {}
+                    #     for i in range(len(parents)):
+                    #         data[f"parent{i + 1}"] = parents[i]
+                    #     data["offspring"] = offspring
+                    #     with open(self.output_path + "/results/history/pop_" + str(pop + 1) + "_" + str(
+                    #             na) + "_" + op + ".json", "w") as file:
+                    #         json.dump(data, file, indent=5)
+                    # populatin management
+                    size_act = min(len(population), self.pop_size)
+                    population = self.manage.population_management(population, size_act)
+                    print()
 
 
             # Save population to a file
@@ -182,4 +182,3 @@ def run(self):
             for i in range(len(population)):
                 print(str(population[i]['objective']) + " ", end="")
             print()
-
diff --git a/eoh/src/eoh/methods/localsearch/ls.py b/eoh/src/eoh/methods/localsearch/ls.py
index e8d4474c..277799c7 100644
--- a/eoh/src/eoh/methods/localsearch/ls.py
+++ b/eoh/src/eoh/methods/localsearch/ls.py
@@ -138,8 +138,7 @@ def run(self):
                 op_w = self.operator_weights[i]
                 if (np.random.rand() < op_w):
                     parents, offsprings = interface_ec.get_algorithm(population, op)
-                    
-                self.manage.population_management(population,offsprings[0],temperature)
+                    self.manage.population_management(population,offsprings[0],temperature)
 
             # Save population to a file
             filename = self.output_path + "/results/pops/population_generation_" + str(pop + 1) + ".json"
@@ -157,4 +156,3 @@ def run(self):
             for i in range(len(population)):
                 print(str(population[i]['objective']) + " ", end="")
             print()
-
diff --git a/eoh/src/eoh/utils/getParas.py b/eoh/src/eoh/utils/getParas.py
index e9d33982..79bfe9a8 100644
--- a/eoh/src/eoh/utils/getParas.py
+++ b/eoh/src/eoh/utils/getParas.py
@@ -79,8 +79,8 @@ def set_ec(self):
 
         if self.ec_operator_weights == None:
             self.ec_operator_weights = [1 for _ in range(len(self.ec_operators))]
-        elif len(self.ec_operator) != len(self.ec_operator_weights):
-            print("Warning! Lengths of ec_operator_weights and ec_operator shoud be the same.")
+        elif len(self.ec_operators) != len(self.ec_operator_weights):
+            print("Warning! Lengths of ec_operator_weights and ec_operators should be the same.")
             self.ec_operator_weights = [1 for _ in range(len(self.ec_operators))]
                     
         if self.method in ['ls','sa'] and self.ec_pop_size >1: