@Paul: Convex nonlinear constraints can be linearized, and may thus be feasible to model in TIMES using e.g. dummy variables and user constraints. In special cases of general interest, automatic linearization can also be implemented in TIMES, as has been done for example for elastic demand functions.
If I understood you correctly, your constraints are non-convex non-linear, which can only be modelled with global non-linear solvers or with MIP, correct? The MIP option is indeed available in TIMES for basically any user-defined purpose, by using dummy discrete capacity processes and user constraints, but using that option might easily get rather clumsy. So, albeit I think in principle the MIP method would be available, I am not able to offer any efficient formulation to your problem.
But if anyone can show your problem does indeed have a convex formulation, I'd be very happy to turn out proven wrong.
If I understood you correctly, your constraints are non-convex non-linear, which can only be modelled with global non-linear solvers or with MIP, correct? The MIP option is indeed available in TIMES for basically any user-defined purpose, by using dummy discrete capacity processes and user constraints, but using that option might easily get rather clumsy. So, albeit I think in principle the MIP method would be available, I am not able to offer any efficient formulation to your problem.
But if anyone can show your problem does indeed have a convex formulation, I'd be very happy to turn out proven wrong.