Approximating separable nonlinear functions via mixed zero-one programs

Authors:
Manfred Padberg
Affiliations:
Room 517, Statistics and Operations Research Department, New York University, 40 West 4th Street, New York, NY 10003, USA
Venue:
Operations Research Letters
Year:
2000

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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.