Review of Mixed-Integer Nonlinear and Generalized Disjunctive Programming Methods Francisco Trespalacios Ignacio E. Grossmann 10.1184/R1/6467399.v1 https://kilthub.cmu.edu/articles/journal_contribution/Review_of_Mixed-Integer_Nonlinear_and_Generalized_Disjunctive_Programming_Methods/6467399 <p>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.</p> 2014-02-01 00:00:00 Generalized disjunctive programming Mixed-integer nonlinear programming Nonlinear programming Optimization