Improved binary parameters using GA for multi-component aromatic extraction: NRTL model without and with closure equations

Sahoo, Ranjan Kumar; Banerjee, Tamal; Ahmad, Syed Akhlaq; Khanna, Ashok

doi:10.1016/j.fluid.2005.11.006

Cited by 45 publications

(31 citation statements)

References 28 publications

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“…7 shows the comparison of the performance of Simulated Annealing (SA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolution (DE) [13] and HS method for parameter estimation using LS formulation. It is convenient to note that previous studies have reported a robust performance of DE [13], PSO [14,[32][33][34], SA [11,13,32] and GA [12,35] for solving global optimization problems in the modeling of phase equilibrium including parameter estimation problems. To directly examine and compare the performance of HS with those obtained for other stochastic methods using LS approach, we keep their numerical efforts the same via NFE and analyze the results obtained in terms of GSR.…”

Section: Performance Of Traditional Hs Methodsmentioning

confidence: 99%

On the capabilities and limitations of harmony search for parameter estimation in vapor–liquid equilibrium modeling

Bonilla-Petriciolet

2012

Fluid Phase Equilibria

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Section: Performance Of Traditional Hs Methodsmentioning

confidence: 99%

On the capabilities and limitations of harmony search for parameter estimation in vapor–liquid equilibrium modeling

Bonilla-Petriciolet

2012

Fluid Phase Equilibria

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“…are often used to solve phase equilibrium problems. But because the search space is highly nonlinear consisting of local and global minima's, the local methods may converge to a local optimum point (Stragevitch and Davila 1997;Sahoo et al 2006). In recent past the stochastic optimization techniques (such as differential evolution (DE), genetic algorithms (GA), simulated annealing (SA), particle swarm algorithm, etc.)…”

Section: Introductionmentioning

confidence: 99%

“…They proved that their results were better than local search methods. In another study (Sahoo et al 2006;Sahoo et al 2007), GA was used to estimate ternary, quaternary and quinary LLE interaction parameters for NRTL and UNIQUAC models. It was reported that GA results were better than other techniques.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Process Design Problems Using Differential Evolution Algorithm

2016

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A modified differential evolution algorithm (MDE) has been used for solving different process related design problems (namely calculation of the NRTL and Two-Suffix Margules activity coefficient models parameters in 20 ternary extraction systems including different ionic liquids and reactor network design problem). The obtained results, in terms of root mean square deviations (rmsd) for these models are satisfactory, with the overall values of 0.0023 and 0.0170 for 169 tie-lines for NRTL and Two-Suffix Margules models, respectively. The results showed that the MDE algorithm results in better solutions compared to the previous work based on genetic algorithm (GA) for correlating liquid-liquid equilibrium (LLE) data in these systems. MDE also outperformed DE algorithm when tested on reactor network design problem with respect to convergence and speed.

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“…In recent years, stochastic global optimization methods have been used extensively in fluid phase equilibrium problems and parameter estimation of models. Among these methods, GA is the most widely used (Alvarez et al 2008;Bonilla-Petriciolet et al 2013;Chamkalani et al 2013;Maddinelli and Pavoni 2013;Rangaiah 2001;Singh et al 2005;Sahoo et al 2006;Sahoo et al 2007;Tan et al 2014;Vakili-Nezhaad et al 2013;Vakili-Nezhaad et al 2014;Vatani et al 2012a;Vatani et al 2012b;Xue et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Experimental and Modeling Investigations of the Viscosity of Crude Oil Binary Blends: New Models Based on the Genetic Algorithm Method

2015

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Abstract:Achieving an estimation of viscosity in crude oil binary mixtures is often difficult because the relationship of viscosity, to the fraction of each crude oil, and many other parameters and constants is comply. This relationship can be expressed by mathematical models with different variables. Besides the known models for predicting the viscosity of crude oil mixtures, the petroleum industry demands other models which give accurate predictions. In this work, two new empirical models have been developed for the calculation of the viscosity of binary crude oil blends. Two techniques-least square (LS) and genetic algorithm (GA)-were used to determine the parameters of the proposed models. Dynamic viscosity of 12 sets of crude oil blends at 298.15 K and 25 different shear rates were measured, resulting in 300 sets of binary data. Moreover, 700 sets of kinematic viscosity binary data were collected from literature sources and used along with 200 of the 300 sets of experimental binary data with a wide range of American Petroleum Institute (API) gravity (9.89-41.2) and viscosity (1.054-165,860 cSt) to examine existing available models as well as the newly developed models in this study. The remaining 100 experimental data points which were not used in the regression process were used for validating the models. The results in terms of the absolute average relative deviation (AARD%) were 33. 546 and 14.195 for the LS method and 13.113 and 13.672 for the GA method for proposed models one and two, respectively. The results of statistical parameters based on the GA and LS methods showed that the GA is a superior method for new model parameter estimation as compared with the traditional LS technique. The GA-based models developed in this study provided the highest accuracy for viscosity calculation of the crude oil blends over all existing models in the literature.

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Improved binary parameters using GA for multi-component aromatic extraction: NRTL model without and with closure equations

Cited by 45 publications

References 28 publications

On the capabilities and limitations of harmony search for parameter estimation in vapor–liquid equilibrium modeling

On the capabilities and limitations of harmony search for parameter estimation in vapor–liquid equilibrium modeling

Optimization of Process Design Problems Using Differential Evolution Algorithm

Experimental and Modeling Investigations of the Viscosity of Crude Oil Binary Blends: New Models Based on the Genetic Algorithm Method

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