Both global warming and concerns regarding the volatility of fuels market have motivated research on renewable fuels. Initially, the search for candidate biofuel components focused on finding molecules, or groups of molecules with properties closely resembling those of fossil fuels. This goal has been changing in recent years and a new paradigm has emerged. Instead of looking to mimic fossil fuels, we are now interested in designing renewable fuels that outperform them. Specifically, we are interested in fuels that can be produced economically while simultaneously displaying superior quality. To achieve this vision, it is necessary to integrate information and methods from three fundamental areas: catalysis, fuel property modeling, and process systems engineering. Our goal is to develop tools that enable the integration of advances in these three areas. We envision that this integrated approach will allow engineers to attack simultaneously the problems of process and fuel design. Methodologically we rely on the formulation of mixed integer non-linear optimization problems to represent the process and fuel design tasks. More specifically we are interested in the development of superstructure-based optimization approaches able to represent the process synthesis and fuel design problems.