Windows fatal exception: integer overflow - using MIP and CBC

I run a model optimization using CBC which terminates with exit code -1073741675, and when running the model as a test case using pytest it returns Windows fatal exception: integer overflow.
By refactoring the first constraint of the model (divide by 123 to make the comp4 coefficient 1) the solver returns an optimal solution.

I have created a reduced version of my model which also produces the error. The .LP file I use looks like this:
```
\Problem name: CBC

Minimize
OBJROW: abs_disp_comp1 + abs_disp_comp2 + abs_disp_comp3 + abs_turn_comp3 + abs_disp_comp4 + abs_disp_comp5 + abs_turn_comp5
Subject To
constr(1): 123 comp4 -14595000000 minInd_comp4 <= 2166172585
constr(2): 109 comp1 - abs_disp_comp1 <= 4932154
constr(3): -109 comp1 - abs_disp_comp1 <= -4932154
constr(4): 109 comp2 - abs_disp_comp2 <= -15299006
constr(5): -109 comp2 - abs_disp_comp2 <= 15299006
constr(6): 98 comp3 - abs_disp_comp3 <= -12877413
constr(7): -98 comp3 - abs_disp_comp3 <= 12877413
constr(8): 98 comp3 - abs_turn_comp3 <= -0
constr(9): -98 comp3 - abs_turn_comp3 <= 0
constr(10): 123 comp4 - abs_disp_comp4 <= 79205599
constr(11): -123 comp4 - abs_disp_comp4 <= -79205599
constr(12): comp5 - abs_disp_comp5 <= -30819408
constr(13): - comp5 - abs_disp_comp5 <= 30819408
constr(14): comp5 - abs_turn_comp5 <= -0
constr(15): - comp5 - abs_turn_comp5 <= 0
Bounds
comp1 Free
comp2 Free
comp3 Free
comp4 Free
comp5 Free
0 <= minInd_comp4 <= 1
abs_disp_comp1 Free
abs_disp_comp2 Free
abs_disp_comp3 Free
abs_turn_comp3 Free
abs_disp_comp4 Free
abs_disp_comp5 Free
abs_turn_comp5 Free
Integers
comp1 comp2 comp3 comp4 comp5 minInd_comp4
End
```

I run it using pytest with the above model_overflow.lp input:
```
import mip
class TestOverflow:
def test_overflow(self):
m = mip.Model(solver_name="CBC")
m.read('model_overflow.lp')
optimization_status = m.optimize()
assert optimization_status == mip.OptimizationStatus.OPTIMAL
```

I would expect the model to be solvable, which it also is if I refactor the constraints. I also tried giving the solver an initial feasible solution with all integer variables set to zero, which didn't change the behavior.

- Operating System, version: Windows 10 Enterprise 10.0.19044 Build 19044
- Python version: 3.9.10
- Python-MIP version (we recommend you to test with the latest version): 1.14.1

I have tried to run the model on linux mint with python 3.10 and that works as expected.