In this article, we propose a new method to reduce the computational burden of strategic supply chain (SC) planning models that provide decision support for public policy makers. The method is based on a rolling horizon strategy where some of the integer variables in the mixed-integer programming model are treated as continuous. By comparing with rigorous solutions, we show that the strategy works efficiently. We illustrate the capabilities of the approach presented by its application to a SC design problem related to the sugar cane industry in Argentina. The case study involves determining the number and type of production and storage facilities to be built in each region of the country so that the ethanol and sugar demand is fulfilled and the economic performance is maximized. (C) 2011 Elsevier Ltd. All rights reserved.