diff --git a/deep_learning4e.py b/deep_learning4e.py
index 9f5b0a8f7..7250751d3 100644
--- a/deep_learning4e.py
+++ b/deep_learning4e.py
@@ -575,7 +575,7 @@ def AutoencoderLearner(inputs, encoding_size, epochs=200, verbose=False):
     model.add(Dense(input_size, activation='relu', kernel_initializer='random_uniform', bias_initializer='ones'))
 
     # update model with sgd
-    sgd = optimizers.SGD(lr=0.01)
+    sgd = optimizers.SGD(learning_rate=0.01)
     model.compile(loss='mean_squared_error', optimizer=sgd, metrics=['accuracy'])
 
     # train the model
diff --git a/gui/tsp.py b/gui/tsp.py
index 590fff354..bbe060499 100644
--- a/gui/tsp.py
+++ b/gui/tsp.py
@@ -260,7 +260,7 @@ def fitness_fn(state):
         while True:
             population = [mutate(recombine(*select(2, population, fitness_fn)), self.mutation_rate.get())
                           for _ in range(len(population))]
-            current_best = np.argmax(population, key=fitness_fn)
+            current_best = utils.argmax_random_ties(population, key=fitness_fn)
             if fitness_fn(current_best) > fitness_fn(all_time_best):
                 all_time_best = current_best
                 self.cost.set("Cost = " + str('%0.3f' % (-1 * problem.value(all_time_best))))