Design and planning of the bioethanol supply chain via simulation-based optimization: the case of Argentina

Guillermo A. Durand, Fernando D. Mele, Gonzalo Guillén-Gosálbez, Alberto Bandoni


This paper addresses the strategic planning of bioethanol supply chains (SC) under uncertainty in the demand. The design problem is setting as a reformulation of a multi-scenario mixed-integer linear programming (MILP) problem. It consists in the adoption of a simulation-based optimization scheme to accommodate the variables belonging to different management levels. The strategy supports decisions 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 capability of the approach is demonstrated through a case study based on the Argentinean sugarcane industry. Results include the investment strategy for the optimal SC configuration.


Supply chain management; Uncertainty; Sugar cane industry.

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