Published

2020-01-01

Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems

Evaluación de un Nuevo Algoritmo de Optimización Multimodal en Problemas de Equilibrio de Fases Fluidas

DOI:

https://doi.org/10.15446/ing.investig.v40n1.78822

Keywords:

multimodal optimization, azeotropy, refrigerant fluids, metaheuristics (en)
optimización multimodal, azeotropía, fluido refrigerante, metaheurística (es)

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Authors

  • Gustavo Mendes Platt Federal University of Rio Grande (FURG) https://orcid.org/0000-0003-0506-2561
  • Marcelo Escobar Aragão Federal University of Rio Grande (FURG)
  • Fernanda Cabral Borges Federal University of Rio Grande
  • Douglas Alves Goulart Federal University of Rio Grande (FURG)
Multimodal optimization problems are commonly found in engineering problems, and their solution can be very challenging for metaheuristic approaches. In this work, the use of a recently proposed multimodal metaheuristic method was analyzed - the Multimodal Flower Pollination Algorithm - in two fluid phase equilibrium problems: (i) the calculation of double azeotropes and (ii) parameter estimation in a thermodynamic model. Two different formulations were also considered in the double azeotropy problem. In the azeotrope calculation, a statistical analysis was conducted in order to verify if the algorithm performance is affected by the the problem formulation. The computational results indicate that the methodology provides robust results and that the objective function employed affects the computational performance.
Los problemas de optimización multimodal se encuentran comúnmente en problemas de ingeniería y su solución puede ser muy desafiante para los enfoques metaheurísticos. En este trabajo se analizó el uso de un método metaheurístico multimodal recientemente propuesto - el Algoritmo Multimodal de Polinización de la Flor - en problemas de equilibrio de fase fluida en dos etapas: (i) el cálculo de azeótropos dobles y (ii) la estimación de parámetros en un modelo termodinámico. También se consideran dos formulaciones diferentes en el problema de doble azeotropía. En el cálculo de azeótropo, se realizó un análisis estadístico para verificar si el desempeño del algoritmo se ve afectado por la formulación del problema. Los resultados computacionales indican que la metodología proporciona resultados robustos y que la función objetivo empleada afecta el rendimiento computacional.

References

Bermeo, L. A., Caicedo, E., Clementi, L. & Vega, J. (2015). Estimation of the particle size distribution of colloids from multiangle dynamic light scattering measurements with particle swarm optimization. Ingeniería e Investigación, 35(1), 49-54. https://doi.org/10.15446/ing.investig.v35n1.45213

Bonilla-Petriciolet, A., Iglesias-Silva, G. & Hall, K. R. (2009). Calculation of homogeneous azeotropes in reactive and non-reactive mixtures using a stochastic optimization approach. Fluid Phase Equilibria, 281(1), 22-31. https://doi.org/10.1016/j.fluid.2009.03.009

Cuevas, E. & Reyna-Orta, A. (2014). A Cuckoo Search Algorithm for Multimodal Optimization. The Scientific World Journal, 2014, 1-20. https://doi.org/10.1155/2014/497514

Derrac, J., García, S., Molina, D. & Herrera, F. (2011). A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intel-ligence algorithms. Swarm and Evolutionary Computation, 1(1), 3-18. https://doi.org/10.1016/j.swevo.2011.02.002

Gálvez, J., Cuevas, E. & Avalos, O. (2017). Flower Pollination Algorithm for Multimodal Optimization. International Journal of Computational Intelligence Systems, 10(1), 627-646. https://doi.org/10.2991/ijcis.2017.10.1.42

García Montoya, C. A. & Mendoza Toro, S. (2011). Implementation of an Evolutionary Algorithm in Planning Investment in a Power Distribution System. Ingeniería e Investigación, 31(suppl. 2), 118-124. Retrieved from: https://revistas.unal.edu.co/index.php/ingeinv/article/view/25222/33726

Gau, C.-Y., Brennecke, J. F. & Stadtherr, M. A. (2000). Reliable nonlinear parameter estimation in VLE modeling. Fluid Phase Equilibria, 168(1), 1-18. https://doi.org/10.1016/S0378-3812(99)00332-5

Guedes, A. L., Moura Neto, F. D. & Platt, G. M. (2015). Prediction of Azeotropic Behaviour by the Inversion of Functions from the Plane to the Plane. The Canadian Journal of Chemical Engineering, 93(5), 914-928. https://doi.org/10.1002/cjce.22152

Mali, N. A., Mali, P. W., Patil, A. P., and Joshi, S. S. (2017). Vapor- Liquid Equilibrium Data for Binary Mixtures of Acetic Acid + Anisole, Acetone + Anisole, and Isopropanol + Anisole at Pressure 96.15 kPa. Journal of Chemical & Engineering Data, 62(3), 947-953. https://doi.org/10.1021/acs.jced.6b00700

Nagarkar, M. P. & Vikhe, G. J. (2016). Optimization of the linear quadratic regulator (LQR) control quarter car suspension system using genetic algorithm. Ingeniería e Investigación, 36(1), 23-30. https://doi.org/10.15446/ing.investig.v36n1.49253

Nelder, J. A. & Mead, R. (1965). A simplex method for function minimization. The Computer Journal, 7(4): 308-313. https://doi.org/10.1093/comjnl/7.4.308

Parrot, D. & Li, X. (2006). Locating and Tracking Multiple Dynamic Optima by a Particle Swarm Model Using Spe-ciation. IEEE Transactions on Evolutionary Computation, 10(4), 440-458. https://doi.org/10.1109/TEVC.2005.859468

Pavlyukevich, I. (2007). Lévy flights, non-local search and simulated annealing. Journal of Computational Physics, 226(2), 1830-1844. https://doi.org/10.1016/j.jcp.2007.06.008

Platt, G. M. (2016). Numerical Experiments with New Metaheuristic Algorithms in Phase Equilibrium Prob-lems. International Journal of Mathematical Modelling and Numerical Optimisation, 7(2), 189-211. https://doi.org/10.1504/IJMMNO.2016.077048

Platt, G. M., Yang, X-S. & Silva Neto, A. J. (2019). Computational Intelligence, Optimization and Inverse Problems With Applications in Engineering. Springer. https://doi.org/10.1007/978-3-319-96433-1

Quan, M., Liu, Q. Z. & Liu, Z. L. (2018). Identification of Insecticidal Constituents from the Essential Oil from the Aerial Parts Stachys riederi var. Japonica. Molecules, 23(5), 1200. https://doi.org/10.3390/molecules23051200

Segura, H., González, R.A. & Wisniak, J. (2005). Comments on Computing all the azeotropes in refrigerant mixtures through equations of state by Naveed Aslam and Aydin K. Sunol [Fluid Phase Equilib., 224 (2004) 97109]. Fluid Phase Equilibria, 236(1-2), 261-266 https://doi.org/10.1016/j.fluid.2005.07.001

Sergeyev, Y. D., Kvasov, D. E. & Mukhametzhanov, M. S. (2018). On the Efficiency of Nature-inspired Metaheuristics in Expensive Global Optimization with Limited Budget. Nature Scientific Reports, 8 (453), 1-9. https://doi.org/10.1038/s41598-017-18940-4

Shen, W. F., Benyounes, H. & Song, J. (2015). Thermodynamic Topological Analysis of Extractive Distillation of Maximum Boiling Azeotropes. Brazilian Journal of Chemical Engineering, 32(4), 957-966. https://doi.org/10.1590/0104-6632.20150324s20140023

Thomsen, R. (2004). Multimodal Optimization Using Crowding-Based Differential Evolution, Proceeding of 2004 Congress on Evolutionary Computation (2, pp. 1382-1389). Portland, OR. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CEC.2004.1331058

Walas, S. (1985). Phase Equilibria in Chemical Engineering. Boston: Butterworth Publishers. https://doi.org/10.1016/B978-0-409-95162-2.50009-9

Wilson, G.M. (1964). Vapor-liquid equilibrium. XI. A new expression for the excess free energy of mixing. Journal of The American Chemical Society, 86(2), 127-130. https://doi.org/10.1021/ja01056a002

Yang, X-S. (2012). Flower Pollination Algorithm for Multimodal Optimization, in Durand-Lose, J. & Jonoska, N. (Eds.): Unconventional Computation and Natural Computation, Lecture Notes in Computer Science, 7445, 240-249. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-32894-7

How to Cite

APA

Platt, G. M., Aragão, M. E., Borges, F. C. & Goulart, D. A. (2020). Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems. Ingeniería e Investigación, 40(1), 27–33. https://doi.org/10.15446/ing.investig.v40n1.78822

ACM

[1]
Platt, G.M., Aragão, M.E., Borges, F.C. and Goulart, D.A. 2020. Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems. Ingeniería e Investigación. 40, 1 (Jan. 2020), 27–33. DOI:https://doi.org/10.15446/ing.investig.v40n1.78822.

ACS

(1)
Platt, G. M.; Aragão, M. E.; Borges, F. C.; Goulart, D. A. Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems. Ing. Inv. 2020, 40, 27-33.

ABNT

PLATT, G. M.; ARAGÃO, M. E.; BORGES, F. C.; GOULART, D. A. Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems. Ingeniería e Investigación, [S. l.], v. 40, n. 1, p. 27–33, 2020. DOI: 10.15446/ing.investig.v40n1.78822. Disponível em: https://revistas.unal.edu.co/index.php/ingeinv/article/view/78822. Acesso em: 30 mar. 2026.

Chicago

Platt, Gustavo Mendes, Marcelo Escobar Aragão, Fernanda Cabral Borges, and Douglas Alves Goulart. 2020. “Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems”. Ingeniería E Investigación 40 (1):27-33. https://doi.org/10.15446/ing.investig.v40n1.78822.

Harvard

Platt, G. M., Aragão, M. E., Borges, F. C. and Goulart, D. A. (2020) “Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems”, Ingeniería e Investigación, 40(1), pp. 27–33. doi: 10.15446/ing.investig.v40n1.78822.

IEEE

[1]
G. M. Platt, M. E. Aragão, F. C. Borges, and D. A. Goulart, “Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems”, Ing. Inv., vol. 40, no. 1, pp. 27–33, Jan. 2020.

MLA

Platt, G. M., M. E. Aragão, F. C. Borges, and D. A. Goulart. “Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems”. Ingeniería e Investigación, vol. 40, no. 1, Jan. 2020, pp. 27-33, doi:10.15446/ing.investig.v40n1.78822.

Turabian

Platt, Gustavo Mendes, Marcelo Escobar Aragão, Fernanda Cabral Borges, and Douglas Alves Goulart. “Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems”. Ingeniería e Investigación 40, no. 1 (January 1, 2020): 27–33. Accessed March 30, 2026. https://revistas.unal.edu.co/index.php/ingeinv/article/view/78822.

Vancouver

1.
Platt GM, Aragão ME, Borges FC, Goulart DA. Evaluation of a New Multimodal Optimization Algorithm in Fluid Phase Equilibrium Problems. Ing. Inv. [Internet]. 2020 Jan. 1 [cited 2026 Mar. 30];40(1):27-33. Available from: https://revistas.unal.edu.co/index.php/ingeinv/article/view/78822

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Copyright (c) 2020 Gustavo Mendes Platt, Marcelo Escobar Aragão, Fernanda Cabral Borges, Douglas Alves Goulart

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