APPROXIMATING SEPARABLE NONLINEAR FUNCTIONS VIA MIXED ZERO-ONE PROGRAMS

Abstract

We discuss two models from the literature that have been developed to formulate piecewise linear approximation of separable nonlinear functions by way of mixed-integer programs. We show that the most commonly proposed method is computationally inferior to a lesser known technique by comparing analytically the linear programming relaxations of the two formulations. A third way of formulating the problem, that shares the advantages of the better of the two known methods, is also proposed.