The systematic study of thermodynamic properties for understanding liquid-liquid equilibrium (LLE) behavior of Ionic Liquids (ILs) is an important research direction. The predictive thermodynamic models are useful tools in this area. However, the optimization problem in this kind of predictive modelling can be very challenging. This work proposes a hybrid optimization method for handling such problems. This method benefits from the robustness of Genetic Algorithm (GA) as a global search technique while complementing it with local search abilities of Nelder-Mead Algorithm (NMA). The proposed algorithm showed quite promising results in estimating the interaction parameters of four thermodynamic models: UNIFAC, ASOG, PDH-UNIFAC and PDH-ASOG. In these models, the long-range contribution is accounted by Pitzer–Debye–Hückel (PDH) equation while the short-range contribution is considered by nonelectrolyte UNIFAC and ASOG. Particularly, LLE phase behavior of two ILs comprising of sulfate-based anions and imidazolium cations is examined for 44 ternary (421 tie-line) systems and the full set of computed parameters by the proposed hybrid method is reported.