Two-stage efficiency-based approach to biofuel supply chain logistics network design under the risk of disruptions

Abstract

This paper deals with a design problem for the biofuel supply chain logistics network (BSCLN) under the risk of disruptions. Under a circumstance of disruptions, the BSCLN design problem should deal with multiple goals. This paper proposes an innovative procedure for combining a goal programming (GP) approach and the two-stage network data envelopment analysis (NDEA). The GP model will generate various BSCLN configurations that depend on the weights assigned to the goals. Then, the two-stage NDEA is applied to find the overall efficiency of BSCLN and to identify most efficient BSCLN schemes. Through a case study using the real data on the disaster events in South Carolina, the applicability of the proposed procedure is demonstrated. It is observed that the proposed procedure performs well with respect to designing and identifying the efficient and robust BSCLN schemes, which would be able to attract potential investors who are interested in investing in the biofuel industry.