# Finding an optimized set of transformations for convexifying nonconvex MINLP problems

A4 Conference proceedings

Internal Authors/Editors

Publication Details

List of Authors: Lundell, Andreas, Westerlund, Tapio

Editors: Iftekhar A Karimi, Rajagopalan Srinivasan

Place: Amsterdam

Publication year: 2012

Journal: Computer Aided Chemical Engineering

Publisher: Elsevier

Book title: 11th International Symposium on Process Systems Engineering

Journal acronym: COMPUT-AIDED CHEM EN

Title of series: European Symposium on Computer Aided Process Engineering

Volume number: 31

Start page: 1497

End page: 1501

Number of pages: 5

ISBN: 978-0-444-59505-8

ISSN: 1570-7946

Abstract

In this paper we describe a method for obtaining sets of transformations for reformulating a mixed integer nonlinear programming (MINLP) problem containing nonconvex twice-differentiable (C-2) functions to a convex MINLP problem in an extended variable space. The method for obtaining the transformations is based on solving a mixed integer linear programming (MILP) problem given the structure of the nonconvex MINLP problem. The solution of the MILP problem renders a minimal set of transformations convexifying the nonconvex problem. This technique is implemented as an part of the alpha signomial global optimization algorithm (alpha SGO), a global optimization algorithm for nonconvex MINLP problems.

Keywords

global optimization, nonconvex MINLP problems, reformulation techniques, signomial functions