TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization

Tutkimustuotosvertaisarvioitu

Standard

Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization. / Nogueira, Idelfonso B.R.; Martins, Márcio A.F.; Requião, Reiner; Oliveira, Amanda R.; Viena, Vinícius; Koivisto, Hannu; Rodrigues, Alírio E.; Loureiro, José M.; Ribeiro, Ana M.

julkaisussa: COMPUTERS AND INDUSTRIAL ENGINEERING, Vuosikerta 135, 01.09.2019, s. 368-381.

Tutkimustuotosvertaisarvioitu

Harvard

Nogueira, IBR, Martins, MAF, Requião, R, Oliveira, AR, Viena, V, Koivisto, H, Rodrigues, AE, Loureiro, JM & Ribeiro, AM 2019, 'Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization', COMPUTERS AND INDUSTRIAL ENGINEERING, Vuosikerta. 135, Sivut 368-381. https://doi.org/10.1016/j.cie.2019.06.020

APA

Nogueira, I. B. R., Martins, M. A. F., Requião, R., Oliveira, A. R., Viena, V., Koivisto, H., ... Ribeiro, A. M. (2019). Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization. COMPUTERS AND INDUSTRIAL ENGINEERING, 135, 368-381. https://doi.org/10.1016/j.cie.2019.06.020

Vancouver

Nogueira IBR, Martins MAF, Requião R, Oliveira AR, Viena V, Koivisto H et al. Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization. COMPUTERS AND INDUSTRIAL ENGINEERING. 2019 syys 1;135:368-381. https://doi.org/10.1016/j.cie.2019.06.020

Author

Nogueira, Idelfonso B.R. ; Martins, Márcio A.F. ; Requião, Reiner ; Oliveira, Amanda R. ; Viena, Vinícius ; Koivisto, Hannu ; Rodrigues, Alírio E. ; Loureiro, José M. ; Ribeiro, Ana M. / Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization. Julkaisussa: COMPUTERS AND INDUSTRIAL ENGINEERING. 2019 ; Vuosikerta 135. Sivut 368-381.

Bibtex - Lataa

@article{629c59344ea04afca28448880ad94014,
title = "Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization",
abstract = "The optimization of Simulated Moving Bed units has become an important topic to be developed in this field. The present work proposes a novel methodology to optimize a True Moving Bed unit and draw the feasible operating region through a novel improved Self-Organizing Hierarchical Particle Swarm Optimization with Time-Varying Acceleration Coefficients and Mutable Searching Region, here called Sliding Particle Swarm Optimization, concomitantly with an adapted method to define the feasible operating region. Two main contributions can be highlighted, first the process optimization with its feasible operational regions, leading to better results when compared with the numerical optimization based on the equilibrium theory, second a new particle swarm method is presented which can deal more efficiently with multi local minima problems. Finally, the concept of feasible operating region concept is presented as a support tool for the process operation. Three different operational scenarios were simulated here in order to verify the consistence and efficiency of the methodology. The main advantage of the methodology here proposed is the possibility to tracking all the possible operating regime of the unit while meeting a given process requirement.",
keywords = "Enantiomers separation, Feasible operating region, Particle Swarm Optimization, True Moving Bed",
author = "Nogueira, {Idelfonso B.R.} and Martins, {M{\'a}rcio A.F.} and Reiner Requi{\~a}o and Oliveira, {Amanda R.} and Vin{\'i}cius Viena and Hannu Koivisto and Rodrigues, {Al{\'i}rio E.} and Loureiro, {Jos{\'e} M.} and Ribeiro, {Ana M.}",
year = "2019",
month = "9",
day = "1",
doi = "10.1016/j.cie.2019.06.020",
language = "English",
volume = "135",
pages = "368--381",
journal = "COMPUTERS AND INDUSTRIAL ENGINEERING",
issn = "0360-8352",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization

AU - Nogueira, Idelfonso B.R.

AU - Martins, Márcio A.F.

AU - Requião, Reiner

AU - Oliveira, Amanda R.

AU - Viena, Vinícius

AU - Koivisto, Hannu

AU - Rodrigues, Alírio E.

AU - Loureiro, José M.

AU - Ribeiro, Ana M.

PY - 2019/9/1

Y1 - 2019/9/1

N2 - The optimization of Simulated Moving Bed units has become an important topic to be developed in this field. The present work proposes a novel methodology to optimize a True Moving Bed unit and draw the feasible operating region through a novel improved Self-Organizing Hierarchical Particle Swarm Optimization with Time-Varying Acceleration Coefficients and Mutable Searching Region, here called Sliding Particle Swarm Optimization, concomitantly with an adapted method to define the feasible operating region. Two main contributions can be highlighted, first the process optimization with its feasible operational regions, leading to better results when compared with the numerical optimization based on the equilibrium theory, second a new particle swarm method is presented which can deal more efficiently with multi local minima problems. Finally, the concept of feasible operating region concept is presented as a support tool for the process operation. Three different operational scenarios were simulated here in order to verify the consistence and efficiency of the methodology. The main advantage of the methodology here proposed is the possibility to tracking all the possible operating regime of the unit while meeting a given process requirement.

AB - The optimization of Simulated Moving Bed units has become an important topic to be developed in this field. The present work proposes a novel methodology to optimize a True Moving Bed unit and draw the feasible operating region through a novel improved Self-Organizing Hierarchical Particle Swarm Optimization with Time-Varying Acceleration Coefficients and Mutable Searching Region, here called Sliding Particle Swarm Optimization, concomitantly with an adapted method to define the feasible operating region. Two main contributions can be highlighted, first the process optimization with its feasible operational regions, leading to better results when compared with the numerical optimization based on the equilibrium theory, second a new particle swarm method is presented which can deal more efficiently with multi local minima problems. Finally, the concept of feasible operating region concept is presented as a support tool for the process operation. Three different operational scenarios were simulated here in order to verify the consistence and efficiency of the methodology. The main advantage of the methodology here proposed is the possibility to tracking all the possible operating regime of the unit while meeting a given process requirement.

KW - Enantiomers separation

KW - Feasible operating region

KW - Particle Swarm Optimization

KW - True Moving Bed

U2 - 10.1016/j.cie.2019.06.020

DO - 10.1016/j.cie.2019.06.020

M3 - Article

VL - 135

SP - 368

EP - 381

JO - COMPUTERS AND INDUSTRIAL ENGINEERING

JF - COMPUTERS AND INDUSTRIAL ENGINEERING

SN - 0360-8352

ER -