Process synthesis under uncertainty via multi-parametric programming

Luis F. Domínguez, Efstratios N. Pistikopoulos

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In this work we propose a multi-parametric mixed-integer quadratic-approximation algorithm for the solution of convex multi-parametric mixed-integer nonlinear programming problems arising in process synthesis under uncertainty. The algorithm follows a decomposition procedure where a primal sub-problem is solved using multiparametric nonlinear programming techniques and a master sub-problem is solved using a mixed-inter-nonlinear programming formulation. An example problem is presented to illustrate the proposed algorithm. © 2010 Elsevier B.V. All rights reserved.
Original languageEnglish (US)
Pages (from-to)1123-1128
Number of pages6
JournalComputer Aided Chemical Engineering
Issue numberC
StatePublished - 2010
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2021-07-01
Acknowledgements: Financial support from the Mexican Council for Science and Technology (CONACyT), European Union (PROMATCH Marie Curie MRTN-CT-2004-512441), European Research Council (MOBILE, ERC Advanced Grant, No: 226462), KAUST and the CPSE Industrial Consortium is gratefully acknowledged.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • General Chemical Engineering
  • Computer Science Applications


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