Phase Equilibrium Data Reconciliation Using Multi‐Objective Differential Evolution with Tabu List

In this chapter, multi-objective optimization is employed for simultaneous parameter estimation and data reconciliation in phase equilibrium modeling. Specifically, we have analyzed the advantages and capabilities of multi-objective optimization for data reconciliation of vapor-liquid equilibrium using the error-in-variable formulation and activity coefficient models. A multi-objective optimization method based on differential evolution with tabu list is used to obtain the Pareto-optimal front in data reconciliation problems with three and four objectives. Finally, the application of some criteria of interest in thermodynamic modeling is illustrated to characterize the solutions obtained from the Pareto-optimal front of reconciled phase equilibrium data. In summary, the results show that multi-objective optimization is an alternative approach for performing data reconciliation in phase equilibrium modeling.