A modular approach to the formulation and a solution of mixed-integer non-linear programming (MINLP) problems are presented, which reduce the size of MINLP and the computational expenses effectively. The method decomposes the synthesis task into three hierarchical levels-the superstructure, the structure, and the modules, with the layer of modules being the most critical to the problem solution. The strategy has been implemented in a simulation environment in which the variables of interest are defined as implicit functions of the optimization variables. The implicit relationships are handled using a data-oriented process simulation technique (DOPS) that significantly simplify the simulation. The method has been effectively applied to two case studies, one from literature for the synthesis of hydrodesalkylation, and another from industrial process manufacturing methylene diphenylene diisocyanates.