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Review of Mixed-Integer Nonlinear and Generalized Disjunctive Programming Methods

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journal contribution
posted on 01.02.2014, 00:00 authored by Francisco Trespalacios, Ignacio E. Grossmann

This work presents a review of the main deterministic mixed-integer nonlinear programming (MINLP) solution methods for problems with convex and nonconvex functions. An overview for deriving MINLP formulations through generalized disjunctive programming (GDP), which is an alternative higher-level representation of MINLP problems, is also presented. A review of solution methods for GDP problems is provided. Some relevant applications of MINLP and GDP in process systems engineering are described in this work.


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