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.
Bibliographical noteKAUST 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
- Chemical Engineering(all)
- Computer Science Applications