Algorithm not converging even though solution is not infeasible

[tonysinghmss]

I am using pymoo to do binary integer programming with multiple objectives.
For a given set of data I am getting the output as follows:

==========================================================================================
n_gen  |  n_eval  | n_nds  |     cv_min    |     cv_avg    |      eps      |   indicator  
==========================================================================================
     1 |      166 |      3 |  0.000000E+00 |  2.3554216867 |             - |             -
     2 |      366 |     15 |  0.000000E+00 |  1.4600000000 |  0.5666666667 |         ideal
     3 |      566 |     19 |  0.000000E+00 |  1.3200000000 |  0.0690848227 |             f
WARNING: Mating could not produce the required number of (unique) offsprings!
     4 |      764 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f
     5 |      964 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f
     6 |     1164 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f
     7 |     1364 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f
     8 |     1564 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f
     9 |     1764 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f
    10 |     1964 |     19 |  0.000000E+00 |  1.3200000000 |  0.000000E+00 |             f

WARNING: Mating could not produce the required number of (unique) offsprings!

I am checking infeasibility using the code infeasible = np.any(res.G > 0.). If it is infeasible, I want to avoid calculating hypervolume, if not I want to calculate the hypervolume. In the example shown above, will my way to check infeasibility work ? Also is my way to check infeasibility correct in general ?

[blankjul]

You would have to define the axis as well when using np.any. You can also directly use CV, e.g. np.any(res.CV > 0, axis=1)

[tonysinghmss]

Thanks Julian.