Design and planning of infrastructures for bioethanol and sugar production under demand uncertainty

► We propose a stochastic model for optimizing bioethanol supply chains under uncertainty in product demand. ► The design task is formulated as a multi-scenario mixed-integer linear programming problem. ► The problem was solved applying the sample average approximation algorithm. ► The capabilities of our approach are demonstrated through a case study based on the Argentinean sugarcane industry. In this paper, we address the strategic planning of integrated bioethanol–sugar supply chains (SC) under uncertainty in the demand. The design task is formulated as a multi-scenario mixed-integer linear programming (MILP) problem that decides on the capacity expansions of the production and storage facilities of the network over time along with the associated planning decisions (i.e., production rates, sales, etc.). The MILP model seeks to optimize the expected performance of the SC under several financial risk mitigation options. This consideration gives a rise to a multi-objective formulation, whose solution is given by a set of network designs that respond in different ways to the actual realization of the demand (the uncertain parameter). The capabilities of our approach are demonstrated through a case study based on the Argentinean sugarcane industry. Results include the investment strategy for the optimal SC configuration along with an analysis of the effect of demand uncertainty on the economic performance of several biofuels SC structures.