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Review of Nonlinear Mixed-Integer and Disjunctive Programming Techniques

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Abstract

This paper has as a major objective to present a unified overview and derivation of mixed-integer nonlinear programming (MINLP) techniques, Branch and Bound, Outer-Approximation, Generalized Benders and Extended Cutting Plane methods, as applied to nonlinear discrete optimization problems that are expressed in algebraic form. The solution of MINLP problems with convex functions is presented first, followed by a brief discussion on extensions for the nonconvex case. The solution of logic based representations, known as generalized disjunctive programs, is also described. Theoretical properties are presented, and numerical comparisons on a small process network problem.

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  1. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Ignacio E. Grossmann

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Grossmann, I.E. Review of Nonlinear Mixed-Integer and Disjunctive Programming Techniques. Optimization and Engineering 3, 227–252 (2002). https://doi.org/10.1023/A:1021039126272

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