8 Satisfying extra constraints with constrained optimization

In previous chapters, we tackled black box optimization problems in which we aimed solely to maximize the objective function, without any other considerations. This is called an unconstrained optimization problem as we are free to explore the search space to look for the global optimum of the objective function. Many real-life situations do not follow this unconstrained formulation, however, and there might be a cost associated with the objective function’s global optimum that makes the optimum infeasible to achieve in practice.

8.1 Accounting for constraints in a constrained optimization problem

8.1.1 Constraints can change the solution of an optimization problem

8.1.2 The constraint-aware BayesOpt framework

8.2 Constraint-aware decision-making in BayesOpt

8.3 Exercise 1: Manual computation of constrained EI

8.4 Implementing constrained EI with BoTorch

8.5 Exercise 2: Constrained optimization of airplane design

Summary