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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 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.

History

Publisher Statement

This is the accepted version of the article which has been published in final form at http://dx.doi.org/10.1002/cite.201400037

Date

01/02/2014

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