Hybrid swarm optimization for vapor-liquid equilibrium modeling

A hybrid algorithm based on particle swarm optimization and ant colony optimization was used to describe the vapor-liquid equilibrium of complex mixtures. The proposed PSO + ACO algorithm is tested on several benchmark functions from the usual literature. Firstly, nine binary vapor-liquid phase systems containing supercritical fluids and ionic liquids were evaluated for optimizing the equation of state method. Next, twenty binary vapor-liquid phase systems were described using two activity coefficient models optimized by the hybrid algorithm. The results of vapor-liquid equilibrium modeling were compared with the Levenberg-Marquardt algorithm, and show that the application of PSO + ACO algorithm on thermodynamic models such as equation of state methods and activity coefficient models, is crucial, and that the hybrid PSO + ACO algorithm is a good tool to optimize the interaction parameters to describe the vapor-liquid equilibrium of several systems. (C) 2014 Elsevier B.V. All rights reserved.