diff --git a/spotpy/examples/tutorial_padds_hymod.py b/spotpy/examples/tutorial_padds_hymod.py
index c239285f..0c2c53d2 100644
--- a/spotpy/examples/tutorial_padds_hymod.py
+++ b/spotpy/examples/tutorial_padds_hymod.py
@@ -123,7 +123,7 @@ def plot_parameter_histogram(ax, results, parameter):
     ax11.plot(q5,color='dimgrey',linestyle='solid')
     ax11.plot(q95,color='dimgrey',linestyle='solid')
     ax11.fill_between(np.arange(0,len(q5),1),list(q5),list(q95),facecolor='dimgrey',zorder=0,
-                    linewidth=0,label='parameter uncertainty')  
+                    linewidth=0,label='parameter uncertainty')
     ax11.plot(spot_setup.evaluation(),'r.',label='data')
     ax11.set_ylim(-50,450)
     ax11.set_xlim(0,729)
diff --git a/tests/test_algorithms.py b/tests/test_algorithms.py
index f6bfce4b..0fbb3f56 100644
--- a/tests/test_algorithms.py
+++ b/tests/test_algorithms.py
@@ -14,15 +14,24 @@
     import spotpy
 import numpy as np
 from spotpy.examples.spot_setup_rosenbrock import spot_setup
-from spotpy.examples.tutorial_padds import padds_spot_setup
+from spotpy.examples.spot_setup_hymod_python import spot_setup as spot_setup_hymod
 from spotpy.describe import describe
 import os
+import numpy as np
 from  spotpy.likelihoods import gaussianLikelihoodMeasErrorOut as GausianLike
 
 
 #https://docs.python.org/3/library/unittest.html
 
 class TestAlgorithms(unittest.TestCase):
+
+    def multi_obj_func(self, evaluation, simulation, params=None):
+        #used to overwrite objective function in hymod example
+        like1 = abs(spotpy.objectivefunctions.bias(evaluation, simulation))
+        like2 = spotpy.objectivefunctions.rmse(evaluation, simulation)
+        like3 = spotpy.objectivefunctions.rsquared(evaluation, simulation)*-1
+        return np.array([like1, like2, like3])
+
     def setUp(self):
         # How many digits to match in case of floating point answers
         self.tolerance = 7
@@ -116,8 +125,16 @@ def test_fast(self):
         self.assertEqual(len(results), self.rep) #Si values should be returned
 
     def test_padds(self):
-        sampler=spotpy.algorithms.padds(padds_spot_setup(),parallel=self.parallel, dbname='RosenPADDS', dbformat=self.dbformat, sim_timeout=self.timeout)
-        sampler.sample(self.rep)
+        sampler=spotpy.algorithms.padds(spot_setup_hymod(self.multi_obj_func),parallel=self.parallel, dbname='Rosen', dbformat=self.dbformat, sim_timeout=self.timeout)
+        sampler.sample(int(self.rep*0.5), metric='ones')
+        results = sampler.getdata()
+        self.assertEqual(len(results)+5, int(self.rep*0.5))
+
+    def test_nsgaii(self):
+        generations=20
+        n_pop = 10
+        sampler=spotpy.algorithms.NSGAII(spot_setup_hymod(self.multi_obj_func),parallel=self.parallel, dbname='Rosen', dbformat=self.dbformat, sim_timeout=self.timeout)
+        sampler.sample(generations, n_obj= 3, n_pop = n_pop)
         results = sampler.getdata()
         self.assertEqual(len(results)+5, self.rep) #Si values should be returned