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Gangwar S, Fernández D, Pozo C, Folgado R, Jiménez L, Boer D. Scheduling optimization and risk analysis for energy-intensive industries under uncertain electricity market to facilitate financial planning. Comput Chem Eng 2023. [DOI: 10.1016/j.compchemeng.2023.108234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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Saini RST, Pappas I, Avraamidou S, Ganesh HS. Noncooperative Distributed Model Predictive Control: A Multiparametric Programming Approach. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.2c03057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Radhe S. T. Saini
- Discipline of Chemical Engineering, Indian Institute of Technology Gandhinagar, Gujarat382055, India
| | - Iosif Pappas
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States
| | - Styliani Avraamidou
- Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin53706, United States
| | - Hari S. Ganesh
- Discipline of Chemical Engineering, Indian Institute of Technology Gandhinagar, Gujarat382055, India
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Daoutidis P, Zhang Q. From Amundson, Aris, and Sargent to the future of process systems engineering. Chem Eng Res Des 2022. [DOI: 10.1016/j.cherd.2022.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Challenges and Opportunities in Carbon Capture, Utilization and Storage: A Process Systems Engineering Perspective. Comput Chem Eng 2022. [DOI: 10.1016/j.compchemeng.2022.107925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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Wang C, Wilhelm ME, Stuber MD. Semi-Infinite Optimization with Hybrid Models. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c00113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Chenyu Wang
- Process Systems and Operations Research Laboratory, Department of Chemical & Biomolecular Engineering, University of Connecticut, 191 Auditorium Road, Unit 3222, Storrs, Connecticut 06269, United States
| | - Matthew E. Wilhelm
- Process Systems and Operations Research Laboratory, Department of Chemical & Biomolecular Engineering, University of Connecticut, 191 Auditorium Road, Unit 3222, Storrs, Connecticut 06269, United States
| | - Matthew D. Stuber
- Process Systems and Operations Research Laboratory, Department of Chemical & Biomolecular Engineering, University of Connecticut, 191 Auditorium Road, Unit 3222, Storrs, Connecticut 06269, United States
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Golpîra H, Javanmardan A. Decentralized Decision System for Closed-Loop Supply Chain: A Bi-Level Multi-Objective Risk-Based Robust Optimization Approach. Comput Chem Eng 2021. [DOI: 10.1016/j.compchemeng.2021.107472] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Abstract
Dynamic flux balance models (DFBM) are used in this study to infer metabolite concentrations that are difficult to measure online. The concentrations are estimated based on few available measurements. To account for uncertainty in initial conditions the DFBM is converted into a variable structure system based on a multiparametric linear programming (mpLP) where different regions of the state space are described by correspondingly different state space models. Using this variable structure system, a special set membership-based estimation approach is proposed to estimate unmeasured concentrations from few available measurements. For unobservable concentrations, upper and lower bounds are estimated. The proposed set membership estimation was applied to batch fermentation of E. coli based on DFBM.
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Cetegen SA, Stuber MD. Optimal design of controlled environment agricultural systems under market uncertainty. Comput Chem Eng 2021. [DOI: 10.1016/j.compchemeng.2021.107285] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Obermeier A, Vollmer N, Windmeier C, Esche E, Repke JU. Generation of linear-based surrogate models from non-linear functional relationships for use in scheduling formulation. Comput Chem Eng 2021. [DOI: 10.1016/j.compchemeng.2020.107203] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Pappas I, Kenefake D, Burnak B, Avraamidou S, Ganesh HS, Katz J, Diangelakis NA, Pistikopoulos EN. Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward. FRONTIERS IN CHEMICAL ENGINEERING 2021. [DOI: 10.3389/fceng.2020.620168] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The inevitable presence of uncertain parameters in critical applications of process optimization can lead to undesirable or infeasible solutions. For this reason, optimization under parametric uncertainty was, and continues to be a core area of research within Process Systems Engineering. Multiparametric programming is a strategy that offers a holistic perspective for the solution of this class of mathematical programming problems. Specifically, multiparametric programming theory enables the derivation of the optimal solution as a function of the uncertain parameters, explicitly revealing the impact of uncertainty in optimal decision-making. By taking advantage of such a relationship, new breakthroughs in the solution of challenging formulations with uncertainty have been created. Apart from that, researchers have utilized multiparametric programming techniques to solve deterministic classes of problems, by treating specific elements of the optimization program as uncertain parameters. In the past years, there has been a significant number of publications in the literature involving multiparametric programming. The present review article covers recent theoretical, algorithmic, and application developments in multiparametric programming. Additionally, several areas for potential contributions in this field are discussed, highlighting the benefits of multiparametric programming in future research efforts.
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Katz J, Pappas I, Avraamidou S, Pistikopoulos EN. Integrating deep learning models and multiparametric programming. Comput Chem Eng 2020. [DOI: 10.1016/j.compchemeng.2020.106801] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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13
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Tsay C, Baldea M. 110th Anniversary: Using Data to Bridge the Time and Length Scales of Process Systems. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b02282] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Calvin Tsay
- McKetta Department of Chemical Engineering The University of Texas at Austin, Austin, Texas 78712, United States
| | - Michael Baldea
- McKetta Department of Chemical Engineering The University of Texas at Austin, Austin, Texas 78712, United States
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Avraamidou S, Pistikopoulos EN. A Multi-Parametric optimization approach for bilevel mixed-integer linear and quadratic programming problems. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.01.021] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Vrabec J, Bernreuther M, Bungartz HJ, Chen WL, Cordes W, Fingerhut R, Glass CW, Gmehling J, Hamburger R, Heilig M, Heinen M, Horsch MT, Hsieh CM, Hülsmann M, Jäger P, Klein P, Knauer S, Köddermann T, Köster A, Langenbach K, Lin ST, Neumann P, Rarey J, Reith D, Rutkai G, Schappals M, Schenk M, Schedemann A, Schönherr M, Seckler S, Stephan S, Stöbener K, Tchipev N, Wafai A, Werth S, Hasse H. SkaSim - Skalierbare HPC-Software für molekulare Simulationen in der chemischen Industrie. CHEM-ING-TECH 2018. [DOI: 10.1002/cite.201700113] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Jadran Vrabec
- Universität Paderborn; Lehrstuhl für Thermodynamik und Energietechnik; Warburger Straße 100 33098 Paderborn Deutschland
| | - Martin Bernreuther
- HLRS Höchstleistungsrechenzentrum Stuttgart; Nobelstraße 19 70569 Stuttgart Deutschland
| | - Hans-Joachim Bungartz
- Technische Universität München; Institut für Informatik; Boltzmannstraße 3 85748 Garching Deutschland
| | - Wei-Lin Chen
- National Taiwan University; Department of Chemical Engineering; No. 1, Section 4, Roosevelt Rd 10617 Taipei City Taiwan
| | - Wilfried Cordes
- DDBST GmbH; Marie-Curie-Straße 10 26129 Oldenburg Deutschland
| | - Robin Fingerhut
- Universität Paderborn; Lehrstuhl für Thermodynamik und Energietechnik; Warburger Straße 100 33098 Paderborn Deutschland
| | - Colin W. Glass
- HLRS Höchstleistungsrechenzentrum Stuttgart; Nobelstraße 19 70569 Stuttgart Deutschland
| | - Jürgen Gmehling
- DDBST GmbH; Marie-Curie-Straße 10 26129 Oldenburg Deutschland
| | - René Hamburger
- Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM; Fraunhofer-Platz 1 67663 Kaiserslautern Deutschland
| | - Manfred Heilig
- BASF SE; Carl-Bosch-Straße 38 67056 Ludwigshafen/Rhein Deutschland
| | - Matthias Heinen
- Universität Paderborn; Lehrstuhl für Thermodynamik und Energietechnik; Warburger Straße 100 33098 Paderborn Deutschland
| | - Martin T. Horsch
- Technische Universität Kaiserslautern; Lehrstuhl für Thermodynamik; Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Deutschland
- American University of Iraq, Sulaimani; Engineering Department; Sulaimani - Kirkuk Road 46001 Raparin, Sulaimani Irak
| | - Chieh-Ming Hsieh
- National Central University; Department of Chemical & Material Engineering; No. 300 Zhongda Road 320 Taoyuan City Taiwan
| | - Marco Hülsmann
- Hochschule Bonn-Rhein-Sieg; Fachbereich Elektrotechnik, Maschinenbau und Technikjournalismus; Grantham-Allee 20 53757 Sankt Augustin Deutschland
- Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI; Schloss Birlinghoven 53757 Sankt Augustin Deutschland
| | - Philip Jäger
- Eurotechnica GmbH; An den Stücken 55 22941 Bargteheide Deutschland
| | - Peter Klein
- Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM; Fraunhofer-Platz 1 67663 Kaiserslautern Deutschland
| | - Sandra Knauer
- Eurotechnica GmbH; An den Stücken 55 22941 Bargteheide Deutschland
| | - Thorsten Köddermann
- Hochschule Bonn-Rhein-Sieg; Fachbereich Elektrotechnik, Maschinenbau und Technikjournalismus; Grantham-Allee 20 53757 Sankt Augustin Deutschland
- Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI; Schloss Birlinghoven 53757 Sankt Augustin Deutschland
| | - Andreas Köster
- Universität Paderborn; Lehrstuhl für Thermodynamik und Energietechnik; Warburger Straße 100 33098 Paderborn Deutschland
| | - Kai Langenbach
- Technische Universität Kaiserslautern; Lehrstuhl für Thermodynamik; Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Deutschland
| | - Shiang-Tai Lin
- National Taiwan University; Department of Chemical Engineering; No. 1, Section 4, Roosevelt Rd 10617 Taipei City Taiwan
| | - Philipp Neumann
- Deutsches Klimarechenzentrum DKRZ; Bundesstraße 45a 20146 Hamburg Deutschland
| | - Jürgen Rarey
- DDBST GmbH; Marie-Curie-Straße 10 26129 Oldenburg Deutschland
| | - Dirk Reith
- Hochschule Bonn-Rhein-Sieg; Fachbereich Elektrotechnik, Maschinenbau und Technikjournalismus; Grantham-Allee 20 53757 Sankt Augustin Deutschland
- Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI; Schloss Birlinghoven 53757 Sankt Augustin Deutschland
| | - Gábor Rutkai
- Universität Paderborn; Lehrstuhl für Thermodynamik und Energietechnik; Warburger Straße 100 33098 Paderborn Deutschland
| | - Michael Schappals
- Technische Universität Kaiserslautern; Lehrstuhl für Thermodynamik; Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Deutschland
| | - Martin Schenk
- Hochschule Bonn-Rhein-Sieg; Fachbereich Elektrotechnik, Maschinenbau und Technikjournalismus; Grantham-Allee 20 53757 Sankt Augustin Deutschland
| | | | | | - Steffen Seckler
- Technische Universität München; Institut für Informatik; Boltzmannstraße 3 85748 Garching Deutschland
| | - Simon Stephan
- Technische Universität Kaiserslautern; Lehrstuhl für Thermodynamik; Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Deutschland
| | - Katrin Stöbener
- Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM; Fraunhofer-Platz 1 67663 Kaiserslautern Deutschland
| | - Nikola Tchipev
- Technische Universität München; Institut für Informatik; Boltzmannstraße 3 85748 Garching Deutschland
| | - Amer Wafai
- HLRS Höchstleistungsrechenzentrum Stuttgart; Nobelstraße 19 70569 Stuttgart Deutschland
| | - Stephan Werth
- Technische Universität Kaiserslautern; Lehrstuhl für Thermodynamik; Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Deutschland
| | - Hans Hasse
- Technische Universität Kaiserslautern; Lehrstuhl für Thermodynamik; Erwin-Schrödinger-Straße 44 67663 Kaiserslautern Deutschland
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Diangelakis NA, Burnak B, Katz J, Pistikopoulos EN. Process design and control optimization: A simultaneous approach by multi-parametric programming. AIChE J 2017. [DOI: 10.1002/aic.15825] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Nikolaos A. Diangelakis
- Centre for Process Systems Engineering, Dept. of Chemical Engineering; Imperial College London; London SW7 2AZ U.K
- Artie McFerrin Dept. of Chemical Engineering; Texas A&M University; College Station TX 77845
- Texas A&M Energy Institute; Texas A&M University; College Station TX 77845
| | - Baris Burnak
- Artie McFerrin Dept. of Chemical Engineering; Texas A&M University; College Station TX 77845
- Texas A&M Energy Institute; Texas A&M University; College Station TX 77845
| | - Justin Katz
- Artie McFerrin Dept. of Chemical Engineering; Texas A&M University; College Station TX 77845
- Texas A&M Energy Institute; Texas A&M University; College Station TX 77845
| | - Efstratios N. Pistikopoulos
- Artie McFerrin Dept. of Chemical Engineering; Texas A&M University; College Station TX 77845
- Texas A&M Energy Institute; Texas A&M University; College Station TX 77845
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