A stochastic programming approach toward optimal design and planning of an integrated green biodiesel supply chain network under uncertainty: A case study

Biodiesel has recently attracted much interest as an appropriate alternative for the fossil diesel which is mostly consumed in the transportation sector. Meanwhile, Jatropha Curcas L. has emerged as one of the most promising biofuel feedstocks due largely to its salient features such as compatibility with arid and semi-arid lands. In this regard, this paper unveils a two-stage stochastic programming model for the design of an integrated green biodiesel supply chain network from Jatropha Curcas feedstocks. The concerned biodiesel supply chain design is an environmentally friendly mixed-integer linear programming, multi-period and multi-product model. Furthermore, a flexible stochastic programming approach is developed and applied to the supply chain network model. This proposed approach is indeed an extension of a two-stage scenario-based stochastic programming approach which incorporates min-max relative regret in a soft worst-case framework. Given the natural variability of long-term decisionmaking, fuel demand and Jatropha Curcas trees yielding are hemmed in by uncertainty in this model. The performance of the proposed framework and biodiesel supply chain network design is corroborated through ten realizations and a myriad of various analyses in a real case study of Iran. The derived results and their analyses acknowledge the efficiency and applicability of the model. (C) 2018 Elsevier Ltd. All rights reserved.