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dc.contributor.authorDomínguez, Luis F.
dc.contributor.authorPistikopoulos, Efstratios N.
dc.date.accessioned2021-06-30T12:52:44Z
dc.date.available2021-06-30T12:52:44Z
dc.date.issued2010
dc.identifier.citationDomínguez, L. F., & Pistikopoulos, E. N. (2010). Process Synthesis under Uncertainity via Multi-parametric Programming. 20th European Symposium on Computer Aided Process Engineering, 1123–1128. doi:10.1016/s1570-7946(10)28188-9
dc.identifier.isbn9780444535696
dc.identifier.issn1570-7946
dc.identifier.doi10.1016/S1570-7946(10)28188-9
dc.identifier.urihttp://hdl.handle.net/10754/669858
dc.description.abstractIn 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.
dc.description.sponsorshipFinancial 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.
dc.publisherElsevier
dc.relation.urlhttps://linkinghub.elsevier.com/retrieve/pii/S1570794610281889
dc.rightsArchived with thanks to Computer Aided Chemical Engineering
dc.titleProcess synthesis under uncertainty via multi-parametric programming
dc.typeArticle
dc.identifier.journal20th European Symposium on Computer Aided Process Engineering
dc.eprint.versionPost-print
dc.contributor.institutionCentre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, SW7 2AZ, United Kingdom
dc.identifier.volume28
dc.identifier.issueC
dc.identifier.pages1123-1128
dc.identifier.eid2-s2.0-78651423581


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