Using genetic algorithm (GA) and particle swarm optimization (PSO) methods for determination of interaction parameters in multicomponent systems of liquid–liquid equilibria

• For the first time, particle swarm optimization (PSO) is used in LLE calculation.
• Systems of three, four and five components have been studied.
• Three thermodynamic models, i.e. Wilson, NRTL and UNIQUAC, are used.
• Genetic algorithm also used for optimization and compared to PSO.

For the prediction of liquid–liquid equilibria (LLE), Wilson, universal quasi chemical (UNIQUAC) and non-random two liquid (NRTL) models were used. Evolutionary algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) were used for estimation of binary interaction parameters of these models. These two optimization methods are rarely used in LLE calculations; as far as we know the PSO algorithm has never been used and it is reported for the first time. For ternary, quaternary and quinary systems, the calculation done and the obtained results are compared to experimental data. The reliability of GA and PSO in LLE applications was successfully approved.

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