Equation-oriented simulators have some advantages over the modular sequential ones, but improvements are still necessary to deal with nonlinearities, while preserving the robustness of the solver. Linear approximations and/or surrogate models can be used in place of nonlinear models, but the loss of predictive accuracy may be a drawback. An alternative to circumvent this problem is the use of grid-based look-up tables for interpolating responses from rigorous models. This methodology was integrated in an equation-oriented simulator (EMSO). A case study involving the production of bioethanol from sugarcane is used to demonstrate the robustness of this approach. Look-up tables replaced the models of two distillation column trains and of the cellulose hydrolysis reactor. These models were included into the global process and an optimization problem aiming at the maximum production of ethanol was successfully solved by a PSO algorithm varying the solid mass fraction in the hydrolysis reactor. (C) 2015 Elsevier Ltd. All rights reserved.