The main objective of this work is to assess the impacts of integrating new biomass conversion technologies into an existing sugarcane industrial processing plant in terms of its multi-objective optimal operating conditions. A typical sugarcane mill is identified and a second generation ethanol production pathway is incorporated to give the operator the possibility of controlling the ratio between the rates of burning bagasse and straw (sugarcane tops and leaves) to their second generation processing to achieve optimal ethanol and electricity outputs. A set of equations describing the associated conversion unit operations and chemical reactions is simulated by the Monte Carlo method and the corresponding operating envelope is constructed and statistically analyzed. These equations permit to calculate ethanol production and electricity generation in terms of a virtually infinite number of scenarios characterized by two controlled variables (burning bagasse and straw mass flow rates) and several uncontrolled variables (biomass composition, cellulose, hemicelluloses and lignin yields, fermentation efficiencies, etc.). Results reveal that the input variables have specific statistical characteristics when the corresponding operating states lay near the maximum energy limit (Pareto frontier). For example, since the objectives being optimized are intrinsically antagonistic, i.e. the increase of one dictates the decrease of the other, it is better to convert bagasse to ethanol via second generation pathway because of the high energy requirements of its dewatering prior to combustion and low heat content of cellulose and hemicelluloses compared with lignin. Another interesting result concerns biomass composition: for both bagasse and straw, higher lignin contents favor simultaneously optimality and robustness.