How to set objective/constraint violation tolerance in Scipy SLSQP?
Found a solution. Instead of using an equality constraint, can change this to an inequality constraint where the constraint, instead of being set to 0, can be set to be less than desired tolerance.
My understanding of SLSQP is that, when it is iterating towards a solution, it simultaneously works to reduce constraint violations and minimize the given function. Since these are two side-by-side processes, I would expect there to be someway to set the tolerance for constraint violation and the tolerance for function minimization separately. Yet the SLSQP documentation doesn't indicate any way to set these two tolerances separately.
For example, in one minimization I may be ok with letting the constraints be violated to the order of 1e-2 while minimizing, yet in another minimization I would want the constraints to be violated with less than 1e-15 of precision. Is there a way to set this?