where f i are the n black-box objective functions, x = (x 1 , . . . , x v ) T represent the v input variables, and lb k and ub k are bounds on the input x k . We focus on multiobjective optimization on a Pareto front , a collection of optimal solutions for each f i such that no single objective can be improved without making at least one of the remaining objectives worse .