GPMixin: trivial constraints created when keep_soft_constraints=False
If a path goal with targets has a timestep for which both the target minimum and target maximum are equal to np.Nan
, when soft constraints are transformed into hard constraints the following type of constraint is created:
-\infty \leq f(x) \leq \infty
.
These turns out to be problematic when using CPLEX. Indeed, CasADi passes the constraint f(x) \leq \infty
to CPLEX which leads to optimization issues when the barrier method is used.