Under what circumstances would you convert an objective into

Under what circumstances would you convert an objective into a constraint?

Solution

constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function with respect to some variables in the presence of constraints on those variables. The objective function is either a cost function or energy function which is to be minimized, or a reward function or utility function, which is to be maximized. Constraints can be either hard constraints which set conditions for the variables that are required to be satisfied, or soft constraints which have some variable values that are penalized in the objective function if, and based on the extent that, the conditions on the variables are not satisfied.

If the objective function and all of the hard constraints are linear, then the problem is a linear programming problem

If all the hard constraints are linear but the objective function is quadratic, the problem is a quadratic programming problem