Bayesian Optimisation with multiple constraints #118
Description
Dear all,
I am trying to do single black box Bayesian optimization with multiple constraints. I followed the tutorial in the https://gpflowopt.readthedocs.io/en/latest/notebooks/constrained_bo.html#Running-Bayesian-Optimizer .
When i solve the optimization with only single constraint i get single optimum solution, but when i do the same for multiple constraints i get solution similiar to multi-objective optimisation ( getting a pareto optimal solution )
https://gpflowopt.readthedocs.io/en/latest/notebooks/multiobjective.html
Here's snippet of code where i am passing the required arguments. First is the objective, while 2nd and 3rd are the black box constraints
self.result = self.opt_pipe.optimize([self.objective, carbide_constraint_upper, carbide_constraint_lower], n_iter=50)
``
I have tried reading the docs but to no avail, please help me in this issue!