diff --git a/Prosumer/main.py b/Prosumer/main.py
index e22fa3296a3332f5ccfcd7af3d03d341a48d9706..98443a195686c6644c3d539a00fb6d6d3f6f8282 100644
--- a/Prosumer/main.py
+++ b/Prosumer/main.py
@@ -283,12 +283,20 @@ class Main:
             self.prosumer[self.name_list[0]].set_components(sector_matrices[self.name_list[0]], self.storage_states, comp_dict[self.name_list[0]])
             global_irradiance, temperature = use_db.config_profiles(input_profiles[name_list[0]], self.t_step)
 
-    def run_optimization(self, name_list):
+    def run_optimization(self, name_list, strategy_name, pareto_set_size, solver_name):
         # ToDo: callback, abbruchbedingung, maybe check the feasebility of the model before building,
         #  häufige fehler bei der eingabe prüfen usw
-        self.prosumer[name_list].run_optimization(strategy_name=['annuity'],
-                                                          solver_name='gurobi',
-                                                          commentary=self.commentary)
+        self.prosumer[name_list].run_optimization(strategy_name=strategy_name,
+                                                          solver_name=solver_name,
+                                                          commentary=self.commentary,
+                                                  pareto_set_size=pareto_set_size)
+
+    #def run_optimization(self, name_list):
+    #    # ToDo: callback, abbruchbedingung, maybe check the feasebility of the model before building,
+    #    #  häufige fehler bei der eingabe prüfen usw
+    #    self.prosumer[name_list].run_optimization(strategy_name=['annuity'],
+    #                                                      solver_name='gurobi',
+    #                                                      commentary=self.commentary)
 
     def show_results(self, name_list, inter_results, final_iteration):
         try:
@@ -377,6 +385,8 @@ class Main:
                 if comp_type == 'Storage':
                     self.charge_status[name_list][components[0]] = all_results.iloc[amount_results-1][('energy', components[0])]\
                                                         /all_results.iloc[amount_results-1][('cap', components[0])]
+            full_results=pd.read_excel('output_files/' + name_list + '/results_' + name_list + '.xlsx')
+            return full_results
         except ValueError:
             print('Results for prosumer ' + name_list + ' cannot be extracted or processed.')
 
diff --git a/Prosumer/model/BaseProsumer.py b/Prosumer/model/BaseProsumer.py
index ab8ff7dc9639bdd6b27764feeaa9600012968281..900f48e882bb72c1e98ac35a39628ab8d9b25df2 100644
--- a/Prosumer/model/BaseProsumer.py
+++ b/Prosumer/model/BaseProsumer.py
@@ -374,7 +374,7 @@ class BaseProsumer:
 
         return pd.DataFrame(np.array(results_lst), columns=columns)
 
-    def run_optimization(self, strategy_name, solver_name='gurobi', commentary=False, pareto_set_size=5):
+    def run_optimization(self, strategy_name, pareto_set_size, solver_name, commentary=False,):
         """
         The method XYZ adds ...
         :param
@@ -382,6 +382,11 @@ class BaseProsumer:
         :returns
         XYZ
         """
+        print('======================================')
+        print('Strategy chosen is ' + strategy_name[0])
+        print('pareto_set_size is ' + str(pareto_set_size))
+        print('solver_name is ' + solver_name)
+        print('======================================')
         self._build_math_model(strategy_name, components)
         # todo: necessary solver options (midgap, ...) should be available from runme.py
         solver = pyo.SolverFactory(solver_name)