Process synthesis under uncertainty via multi-parametric programming

Luis F. Domínguez; Efstratios N. Pistikopoulos

doi:10.1016/S1570-7946(10)28188-9

Process synthesis under uncertainty via multi-parametric programming

Luis F. Domínguez, Efstratios N. Pistikopoulos

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	1123-1128
Number of pages	6
Journal	Computer Aided Chemical Engineering
Volume	28
Issue number	C
DOIs	https://doi.org/10.1016/S1570-7946(10)28188-9
State	Published - 2010
Externally published	Yes

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

Access to Document

10.1016/S1570-7946(10)28188-9

Cite this

@article{1fa421d7da674602bf33efb7ff937279,

title = "Process synthesis under uncertainty via multi-parametric programming",

abstract = "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. {\textcopyright} 2010 Elsevier B.V. All rights reserved.",

author = "Dom{\'i}nguez, {Luis F.} and Pistikopoulos, {Efstratios N.}",

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.",

year = "2010",

doi = "10.1016/S1570-7946(10)28188-9",

language = "English (US)",

volume = "28",

pages = "1123--1128",

journal = "Computer Aided Chemical Engineering",

issn = "1570-7946",

publisher = "Elsevier",

number = "C",

}

TY - JOUR

T1 - Process synthesis under uncertainty via multi-parametric programming

AU - Domínguez, Luis F.

AU - Pistikopoulos, Efstratios N.

N1 - 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.

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/669858

UR - https://linkinghub.elsevier.com/retrieve/pii/S1570794610281889

UR - http://www.scopus.com/inward/record.url?scp=78651423581&partnerID=8YFLogxK

U2 - 10.1016/S1570-7946(10)28188-9

DO - 10.1016/S1570-7946(10)28188-9

M3 - Article

SN - 1570-7946

VL - 28

SP - 1123

EP - 1128

JO - Computer Aided Chemical Engineering

JF - Computer Aided Chemical Engineering

IS - C

ER -

Process synthesis under uncertainty via multi-parametric programming

Abstract

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this