Fossil fuel depletion and the increase of greenhouse gases emissions has been pushing the search for alternative fuels for automotive transport. The European Union has identified biofuel technology as one option for reducing its dependence on imported energy. Ethanol is a promising biofuel, but great uncertainty on the business profitability has recently determined a slowdown in the industry expansion. In particular, geographical plant location, biomass price fluctuation and fuel demand variability severely constrain the economic viability of new ethanol facilities. In this work a dynamic, spatially explicit and multi-echelon Mixed Integer Linear Program (MILP) modeling framework is presented to help decision-makers and potential investors assessing economic performances and risk on investment of the entire biomass-based ethanol supply chain. A case study concerning the corn-to-ethanol production supply chain in Northern Italy is used to demonstrate the effectiveness of the proposed modeling approach. The mathematical pattern addresses the issue of optimizing the ethanol supply network over a ten years' time period under uncertainty on biomass production cost and product selling price. The model allows optimizing economic performances and minimize financial risk on investment by identifying the best network topology in terms of biomass cultivation site locations, ethanol production plant capacities, location and transport logistics. (C) 2011 Elsevier Ltd. All rights reserved.