Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward
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. Multiparam...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-01-01
|
| Series: | Frontiers in Chemical Engineering |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fceng.2020.620168/full |
| _version_ | 1819297960199979008 |
|---|---|
| author | Iosif Pappas Iosif Pappas Dustin Kenefake Dustin Kenefake Baris Burnak Baris Burnak Styliani Avraamidou Hari S. Ganesh Justin Katz Justin Katz Nikolaos A. Diangelakis Nikolaos A. Diangelakis Efstratios N. Pistikopoulos Efstratios N. Pistikopoulos |
| author_facet | Iosif Pappas Iosif Pappas Dustin Kenefake Dustin Kenefake Baris Burnak Baris Burnak Styliani Avraamidou Hari S. Ganesh Justin Katz Justin Katz Nikolaos A. Diangelakis Nikolaos A. Diangelakis Efstratios N. Pistikopoulos Efstratios N. Pistikopoulos |
| author_sort | Iosif Pappas |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-24T05:22:18Z |
| format | Article |
| id | doaj.art-557530268f454246ab128b6e76f8efa0 |
| institution | Directory Open Access Journal |
| issn | 2673-2718 |
| language | English |
| last_indexed | 2024-12-24T05:22:18Z |
| publishDate | 2021-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemical Engineering |
| spelling | doaj.art-557530268f454246ab128b6e76f8efa02022-12-21T17:13:25ZengFrontiers Media S.A.Frontiers in Chemical Engineering2673-27182021-01-01210.3389/fceng.2020.620168620168Multiparametric Programming in Process Systems Engineering: Recent Developments and Path ForwardIosif Pappas0Iosif Pappas1Dustin Kenefake2Dustin Kenefake3Baris Burnak4Baris Burnak5Styliani Avraamidou6Hari S. Ganesh7Justin Katz8Justin Katz9Nikolaos A. Diangelakis10Nikolaos A. Diangelakis11Efstratios N. Pistikopoulos12Efstratios N. Pistikopoulos13Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesArtie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesArtie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesArtie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesArtie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesArtie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, United StatesTexas A&M Energy Institute, Texas A&M University, College Station, TX, United StatesThe 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.https://www.frontiersin.org/articles/10.3389/fceng.2020.620168/fullmultiparametric programmingexplicit model predictive controlprocess systems engineeringoptimization under uncertaintydata science |
| spellingShingle | Iosif Pappas Iosif Pappas Dustin Kenefake Dustin Kenefake Baris Burnak Baris Burnak Styliani Avraamidou Hari S. Ganesh Justin Katz Justin Katz Nikolaos A. Diangelakis Nikolaos A. Diangelakis Efstratios N. Pistikopoulos Efstratios N. Pistikopoulos Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward Frontiers in Chemical Engineering multiparametric programming explicit model predictive control process systems engineering optimization under uncertainty data science |
| title | Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward |
| title_full | Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward |
| title_fullStr | Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward |
| title_full_unstemmed | Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward |
| title_short | Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward |
| title_sort | multiparametric programming in process systems engineering recent developments and path forward |
| topic | multiparametric programming explicit model predictive control process systems engineering optimization under uncertainty data science |
| url | https://www.frontiersin.org/articles/10.3389/fceng.2020.620168/full |
| work_keys_str_mv | AT iosifpappas multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT iosifpappas multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT dustinkenefake multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT dustinkenefake multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT barisburnak multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT barisburnak multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT stylianiavraamidou multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT harisganesh multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT justinkatz multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT justinkatz multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT nikolaosadiangelakis multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT nikolaosadiangelakis multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT efstratiosnpistikopoulos multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward AT efstratiosnpistikopoulos multiparametricprogramminginprocesssystemsengineeringrecentdevelopmentsandpathforward |