SIMOP (SIMulation for OPtimization) is an application that automatically creates FORTRAN simulation models for the stochastic optimizers MSGA and MSIMPSA. This paper presents the next step in SIMOP's development timeline, namely its expansion to cope with mixer-integer nonlinear problems (MINLP) . From the perspective of MINLP formulations' relevance to the Chemical Engineering field, an introduction to SIMOP's MINLP modeling features is given. Its application is addressed by three case studies. The best results match those previously obtained with MSGA and MSIMPSA when non automatically coded MINLP simulations where employed, thus validating the present approach. The introduction of discrete variables benefits the performance of both stochastic optimizers, contrary to what should a priori be expected, since a MINLP formulation promotes an accurate search on lower and upper bounds for several continuous variables. (C) 2011 Elsevier Ltd. All rights reserved.