I am working on a project about Transportation Network Analysis. My network contains data such as nodes, edges, free-flow travel times, capacity, etc. I need to find the volume of edges (links) by using the Frank-Wolf algorithm. I used scipy.optimize.linprog in my code; however, it returns False for success.
The first code is:
result = optimize.linprog(c_0, A_eq=A, b_eq=b) # min(c_0*x) such that: Ax=b
print(result)
result = np.reshape(result['x'], (k, n))
xa = np.sum(result, axis=0) # initial value of xa
print(xa)
The output of the first code is:
con: array([ 1.17458269e+04, 1.19588056e+03, -5.99940081e+00, 1.19488066e+03,
1.19388076e+03, -5.99940073e+00, -5.99940082e+00, -7.99920106e+00,
-5.99940082e+00, 9.71902933e+02, 9.95900537e+02, -5.99940081e+00,
1.13188696e+03, 8.89911122e+02, 8.51914917e+02, -5.99940084e+00,
-5.99940084e+00, -3.99960052e+00, 8.13918712e+02, 5.33946673e+02,
5.33946673e+02, 6.91930895e+02, -7.99920110e+00, 6.63933691e+02,
1.19688046e+03, 1.15548460e+04, -5.99940084e+00, 1.13488666e+03,
1.17388276e+03, -5.99940081e+00, -5.99940078e+00, -7.99920111e+00,
-5.99940078e+00, 9.91900936e+02, 1.01589854e+03, -5.99940087e+00,
8.11918912e+02, 8.49915117e+02, 8.41915916e+02, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, 1.17388276e+03, 5.33946673e+02,
6.13938684e+02, 6.01939883e+02, -7.99920113e+00, 5.33946673e+02,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
1.19688046e+03, 1.13588656e+03, -5.99940075e+00, 1.10638950e+04,
1.19388076e+03, -5.99940078e+00, -5.99940081e+00, -7.99920113e+00,
-5.99940081e+00, 9.71902933e+02, 9.65903533e+02, -5.99940081e+00,
8.51914917e+02, 8.09919111e+02, 7.51924903e+02, -5.99940082e+00,
-5.99940085e+00, -3.99960056e+00, 7.23927699e+02, 5.53944676e+02,
5.73942679e+02, 5.31946873e+02, -7.99920109e+00, 7.23927699e+02,
1.19688046e+03, 1.17588256e+03, -5.99940085e+00, 1.19488066e+03,
1.13728642e+04, -5.99940079e+00, -5.99940091e+00, -7.99920121e+00,
-5.99940080e+00, 1.02189794e+03, 8.75912520e+02, -5.99940083e+00,
8.21917913e+02, 7.89921108e+02, 7.31926900e+02, -5.99940082e+00,
-5.99940079e+00, -3.99960055e+00, 6.53934690e+02, 7.23927699e+02,
7.33926701e+02, 8.41915916e+02, -7.99920111e+00, 5.33946673e+02,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
9.76902434e+02, 9.95900537e+02, -5.99940080e+00, 9.74902634e+02,
1.02389774e+03, -5.99940083e+00, -5.99940084e+00, -7.99920109e+00,
-5.99940077e+00, 1.22707745e+04, 1.20587957e+03, -5.99940074e+00,
8.11918912e+02, 8.89911122e+02, 1.19188096e+03, -5.99940081e+00,
-5.99940082e+00, -3.99960054e+00, 1.05389474e+03, 8.53914717e+02,
8.13918712e+02, 8.71912920e+02, -7.99920105e+00, 5.33946673e+02,
9.96900437e+02, 1.01589854e+03, -5.99940085e+00, 9.64903632e+02,
8.73912720e+02, -5.99940082e+00, -5.99940080e+00, -7.99920109e+00,
-5.99940080e+00, 1.20187996e+03, 1.21647851e+04, -5.99940083e+00,
8.41915916e+02, 1.18988116e+03, 1.00189994e+03, -5.99940083e+00,
-5.99940081e+00, -3.99960055e+00, 8.53914717e+02, 6.63933691e+02,
5.43945675e+02, 9.91900936e+02, -7.99920107e+00, 9.43905730e+02,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
1.13688646e+03, 8.15918512e+02, -5.99940082e+00, 8.54914617e+02,
8.23917713e+02, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, 8.11918911e+02, 8.45915516e+02, -5.99940086e+00,
1.04109602e+04, 7.79922107e+02, 7.71922906e+02, -5.99940081e+00,
-5.99940082e+00, -3.99960055e+00, 6.13938684e+02, 5.33946673e+02,
5.53944676e+02, 6.01939883e+02, -7.99920111e+00, 1.19388076e+03,
8.96910423e+02, 8.55914517e+02, -5.99940082e+00, 8.14918612e+02,
7.93920709e+02, -5.99940082e+00, -5.99940083e+00, -7.99920109e+00,
-5.99940083e+00, 8.91910922e+02, 1.19588056e+03, -5.99940083e+00,
7.81921907e+02, 1.19888026e+04, 1.19188096e+03, -5.99940082e+00,
-5.99940083e+00, -3.99960055e+00, 1.02389774e+03, 8.53914717e+02,
7.83921708e+02, 8.11918911e+02, -7.99920111e+00, 1.02389774e+03,
8.56914418e+02, 8.45915516e+02, -5.99940082e+00, 7.54924604e+02,
7.33926701e+02, -5.99940083e+00, -5.99940083e+00, -7.99920112e+00,
-5.99940083e+00, 1.19188096e+03, 1.00589954e+03, -5.99940083e+00,
7.71922906e+02, 1.18988116e+03, 1.28107206e+04, -5.99940081e+00,
-5.99940085e+00, -3.99960055e+00, 1.19388076e+03, 1.14388576e+03,
1.03389674e+03, 1.19188096e+03, -7.99920110e+00, 8.23917713e+02,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
8.16918412e+02, 1.17588256e+03, -5.99940082e+00, 7.24927600e+02,
6.53934690e+02, -5.99940085e+00, -5.99940081e+00, -7.99920107e+00,
-5.99940082e+00, 1.05189494e+03, 8.55914517e+02, -5.99940083e+00,
6.11938884e+02, 1.01989814e+03, 1.19188096e+03, -5.99940082e+00,
-5.99940079e+00, -3.99960055e+00, 1.20927923e+04, 1.19388076e+03,
1.00389974e+03, 9.91900936e+02, -7.99920108e+00, 7.23927699e+02,
5.36946374e+02, 5.35946474e+02, -5.99940082e+00, 5.54944576e+02,
7.23927699e+02, -5.99940082e+00, -5.99940081e+00, -7.99920109e+00,
-5.99940082e+00, 8.51914917e+02, 6.65933491e+02, -5.99940082e+00,
5.31946873e+02, 8.49915117e+02, 1.14188596e+03, -5.99940082e+00,
-5.99940080e+00, -3.99960056e+00, 1.19388076e+03, 1.05929421e+04,
1.19388076e+03, 1.19188096e+03, -7.99920110e+00, 5.43945675e+02,
5.36946374e+02, 6.15938485e+02, -5.99940082e+00, 5.74942579e+02,
7.33926701e+02, -5.99940084e+00, -5.99940083e+00, -7.99920110e+00,
-5.99940082e+00, 8.11918911e+02, 5.45945475e+02, -5.99940081e+00,
5.51944876e+02, 7.79922107e+02, 1.03189694e+03, -5.99940080e+00,
-5.99940081e+00, -3.99960056e+00, 1.00389974e+03, 1.19388076e+03,
1.08429171e+04, 1.19188096e+03, -7.99920113e+00, 1.19388076e+03,
6.96930396e+02, 6.05939483e+02, -5.99940082e+00, 5.34946573e+02,
8.43915716e+02, -5.99940083e+00, -5.99940083e+00, -7.99920109e+00,
-5.99940083e+00, 8.71912920e+02, 9.95900537e+02, -5.99940083e+00,
6.01939883e+02, 8.09919111e+02, 1.19188096e+03, -5.99940081e+00,
-5.99940078e+00, -3.99960055e+00, 9.93900736e+02, 1.19388076e+03,
1.19388076e+03, 1.16308384e+04, -7.99920112e+00, 1.02389774e+03,
-2.99970041e+00, -3.99960055e+00, -5.99940082e+00, -4.99950069e+00,
-5.99940082e+00, -5.99940082e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, -7.99920110e+00, -3.99960055e+00, -5.99940082e+00,
-7.99920110e+00, -9.99900137e+00, -7.99920110e+00, -5.99940082e+00,
-5.99940082e+00, -3.99960055e+00, -5.99940082e+00, -5.99940082e+00,
-5.99940082e+00, -7.99920110e+00, -7.99920110e+00, -5.99940082e+00,
6.66933392e+02, 5.35946474e+02, -5.99940082e+00, 7.24927600e+02,
5.33946673e+02, -5.99940081e+00, -5.99940082e+00, -7.99920110e+00,
-5.99940082e+00, 5.31946873e+02, 9.45905530e+02, -5.99940082e+00,
1.19188096e+03, 1.01989814e+03, 8.21917913e+02, -5.99940082e+00,
-5.99940086e+00, -3.99960055e+00, 7.23927699e+02, 5.43945675e+02,
1.19388076e+03, 1.02189794e+03, -7.99920107e+00, 1.05329480e+04])
fun: 4381.002675394279
message: 'The algorithm terminated successfully and determined that the problem is infeasible.'
nit: 4
slack: array([], dtype=float64)
status: 2
success: False
x: array([1.33630125, 1.33630125, 0.72363567, ..., 1.25494354, 1.2520338 ,
1.01759439])
[25.2836661 25.2836661 23.87454089 23.85736666 22.92358045 25.21218089
23.77225208 23.82974501 25.39313184 23.82974501 24.83242583 24.49277083
25.37410372 22.90803073 23.68565375 24.81485143 22.88570538 24.25372542
24.45895798 24.68762057 22.92335758 23.92017804 24.27533126 23.11925871
24.58518598 25.23224542 24.60817148 23.14973545 24.26067157 24.60817148
24.59406271 24.6106668 23.6338265 23.75661862 24.24302036 24.72759441
24.39088079 23.6338265 24.60238281 24.71703015 23.86485208 24.78126498
23.29432843 23.86485208 24.04833536 25.12592644 24.26371588 23.24762732
24.39088079 24.33909973 23.87288055 24.01656751 24.04795658 23.70134198
24.30170872 24.30170872 24.23917449 24.64327592 24.07970166 24.34396678
24.67725583 25.12592644 24.32280263 23.60364009 24.23113127 24.21024173
24.40209124 24.3105531 23.75661862 23.63524614 24.42120405 24.17605304
24.42120405 24.36787799 24.23917449]
The second code (added method:'simplex') is:
result = optimize.linprog(c_0, A_eq=A, b_eq=b, method='simplex') # min(c_0*x) such that: Ax=b
print(result)
result = np.reshape(result['x'], (k, n))
xa = np.sum(result, axis=0) # initial value of xa
print(xa)
The output of the second code is:
con: array([9.350e+03, 0.000e+00, 0.000e+00, 0.000e+00, 1.200e+03, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 2.000e+01, 0.000e+00,
2.400e+02, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 1.000e+01, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 1.036e+04, 0.000e+00, 0.000e+00, 4.000e+01, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 2.000e+01, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
1.000e+02, 0.000e+00, 0.000e+00, 4.200e+02, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 9.810e+03, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
3.000e+01, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 2.000e+02, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 1.020e+04, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 1.200e+02, 2.400e+02, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 2.000e+01, 0.000e+00, 0.000e+00, 5.000e+01, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 1.025e+04, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 5.200e+02, 5.400e+02, 0.000e+00, 0.000e+00,
0.000e+00, 2.000e+01, 0.000e+00, 9.000e+01, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 1.096e+04, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 1.300e+02, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 2.900e+02, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 3.000e+01, 0.000e+00,
9.630e+03, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 1.500e+02, 0.000e+00, 0.000e+00, 0.000e+00, 5.800e+02,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 2.000e+01, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 3.000e+02, 0.000e+00,
0.000e+00, 1.001e+04, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 4.000e+01, 7.900e+02, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 1.000e+01, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 9.970e+03, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 7.800e+02, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 3.600e+02, 0.000e+00, 7.000e+01, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
1.017e+04, 0.000e+00, 4.200e+02, 1.000e+03, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 1.700e+02, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 8.750e+03, 5.600e+02, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 8.000e+01, 0.000e+00, 0.000e+00, 1.600e+02, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 1.031e+04, 0.000e+00, 0.000e+00, 1.900e+02,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 4.000e+02, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 1.200e+02, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 2.100e+02, 1.041e+04, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,
6.700e+02, 5.400e+02, 0.000e+00, 7.300e+02, 5.400e+02, 0.000e+00,
0.000e+00, 0.000e+00, 0.000e+00, 5.400e+02, 9.500e+02, 0.000e+00,
1.200e+03, 1.030e+03, 8.300e+02, 0.000e+00, 0.000e+00, 0.000e+00,
7.300e+02, 5.500e+02, 1.200e+03, 1.030e+03, 0.000e+00, 1.054e+04])
fun: 202134.0
message: "Phase 1 of the simplex method failed to find a feasible solution. The pseudo-objective function evaluates to 1.6e+05 which exceeds the required tolerance of 1e-09 for a solution to be considered 'close enough' to zero to be a basic solution. Consider increasing the tolerance to be greater than 1.6e+05. If this tolerance is unacceptably large the problem may be infeasible."
nit: 1000
slack: array([], dtype=float64)
status: 2
success: False
x: array([1200., 0., 0., ..., 0., 0., 0.])
[11740. 0. 0. 0. 0. 0. 1740. 9690. 0. 0.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0. 11940. 0. 1830. 0.
0. 0. 0. 0. 0. 7910. 0. 0. 0. 0.
5050. 0. 0. 0. 0. 7570. 2220. 0. 0. 0.
0. 0. 0. 0. 0. 0. 9650. 3550. 0. 7170.
0. 0. 0. 0. 0. 0. 120. 0. 0. 0.
0. 0. 0. 0. 0.]
I would appreciate any help in solving this problem.
It was the incidence matrix that caused the problem.
I should use this code:
incMatrixScipy = nx.incidence_matrix(Graph1, oriented=True)
incMatrixNumPy = incMatrixScipy.todense()
Instead of this code:
incMatrixScipy = nx.incidence_matrix(Graph1)
incMatrixNumPy = incMatrixScipy.todense()
I need to add oriented=True to receive the correct incidence matrix because my graph is directed.