In [[mathematical optimization]], '''constrained optimization''' (alsoin some contexts called '''constraint optimization''') seeksis athe solutionprocess minimizingof optimizing an objective function in the presence of [[Constraint (mathematics)|constraints]]: either ''hard constraints'' which are required to be satisfied, or ''soft constraints'' which are penalized in the objective function if, and based on the extent that, they are not satisfied. The objective function is either a [[Loss function|cost function]] which is to be minimized or maximizinga itsfunction, negativesometimes called a [[utility function]], which is to be maximized.
