The sugarcane industry has been responsible in some countries for the production of most of the sugar and ethanol available in the world for internal and external markets. In this sector, ethanol can be produced by fermentation of sugars obtained directly from sugarcane biomass, commonly called 1st generation ethanol. New processes using the enzymatic hydrolysis technology of lignocellulosic residues like bagasse and sugarcane leaves as feedstock can increase the ethanol production in these plants, reducing the land requirements and the environmental of impact biofuels production in large scale. The lignocellulosic ethanol production using enzymatic hydrolysis technology is one of the most promising alternatives of 2nd generation biofuels, due to its high conversion efficiencies and low environment impact. Some problems like high water consumption and enzymes costs must be overcome in order to reach commercial scale. The process integration and thermo-economic optimization of the process can be important for the design of this process in a sugarcane autonomous distillery aiming at the cost and environmental impact reduction. In this paper a process integration of the sugarcane ethanol distillery model is carried out taking into account 1st and 2nd generation processes in the same site using sugars and bagasse as feedstock respectively. Conflictive objectives such as maximization of the electricity or ethanol production are adopted in a multi-objective optimization technique using evolutionary algorithms, in order to provide a set of candidate solutions considering different configurations of the ethanol production process design.