diff --git a/test/optimization/test_qaoa.py b/test/optimization/test_qaoa.py
index 6de119f6d..3eb251fbb 100755
--- a/test/optimization/test_qaoa.py
+++ b/test/optimization/test_qaoa.py
@@ -15,13 +15,15 @@
 import unittest
 from test.optimization import QiskitOptimizationTestCase
 
+import math
 import numpy as np
 from ddt import ddt, idata, unpack
-from qiskit import BasicAer
+from qiskit import BasicAer, QuantumCircuit, execute
 
 from qiskit.optimization.applications.ising import max_cut
 from qiskit.optimization.applications.ising.common import sample_most_likely
 from qiskit.aqua.components.optimizers import COBYLA
+from qiskit.aqua.components.initial_states import Custom, Zero
 from qiskit.aqua.algorithms import QAOA
 from qiskit.aqua import QuantumInstance, aqua_globals
 from qiskit.aqua.operators import X, I
@@ -47,6 +49,8 @@
 M2 = None
 S2 = {'1011', '0100'}
 
+CUSTOM_SUPERPOSITION = [1/math.sqrt(15)] * 15 + [0]
+
 
 @ddt
 class TestQAOA(QiskitOptimizationTestCase):
@@ -161,6 +165,63 @@ def cb_callback(eval_count, parameters, mean, std):
         with self.subTest('Solution'):
             self.assertIn(''.join([str(int(i)) for i in graph_solution]), solutions)
 
+    @idata([
+        [W2, None],
+        [W2, [1.0] + 15*[0.0]],
+        [W2, CUSTOM_SUPERPOSITION]
+    ])
+    @unpack
+    def test_qaoa_initial_state(self, w, init_state):
+        """ QAOA initial state test """
+
+        optimizer = COBYLA()
+        qubit_op, _ = max_cut.get_operator(w)
+
+        init_pt = [0.0, 0.0]  # Avoid generating random initial point
+
+        if init_state is None:
+            initial_state = None
+        else:
+            initial_state = Custom(num_qubits=4, state_vector=init_state)
+
+        quantum_instance = QuantumInstance(BasicAer.get_backend('statevector_simulator'))
+        qaoa_zero_init_state = QAOA(qubit_op, optimizer, initial_point=init_pt,
+                                    initial_state=Zero(qubit_op.num_qubits),
+                                    quantum_instance=quantum_instance)
+        qaoa = QAOA(qubit_op, optimizer, initial_point=init_pt,
+                    initial_state=initial_state, quantum_instance=quantum_instance)
+
+        zero_circuits = qaoa_zero_init_state.construct_circuit(init_pt)
+        custom_circuits = qaoa.construct_circuit(init_pt)
+
+        self.assertEqual(len(zero_circuits), len(custom_circuits))
+
+        backend = BasicAer.get_backend('statevector_simulator')
+        for zero_circ, custom_circ in zip(zero_circuits, custom_circuits):
+
+            z_length = len(zero_circ.data)
+            c_length = len(custom_circ.data)
+
+            self.assertGreaterEqual(c_length, z_length)
+            self.assertTrue(zero_circ.data == custom_circ.data[-z_length:])
+
+            custom_init_qc = custom_circ.copy()
+            custom_init_qc.data = custom_init_qc.data[0:c_length-z_length]
+
+            if initial_state is None:
+                original_init_qc = QuantumCircuit(qubit_op.num_qubits)
+                original_init_qc.h(range(qubit_op.num_qubits))
+            else:
+                original_init_qc = initial_state.construct_circuit()
+
+            job_init_state = execute(original_init_qc, backend)
+            job_qaoa_init_state = execute(custom_init_qc, backend)
+
+            statevector_original = job_init_state.result().get_statevector(original_init_qc)
+            statevector_custom = job_qaoa_init_state.result().get_statevector(custom_init_qc)
+
+            self.assertEqual(statevector_original.tolist(), statevector_custom.tolist())
+
 
 if __name__ == '__main__':
     unittest.main()