Chance Constrained Optimization of Biodiesel Supply Chain

Abstract

Biodiesel is an alternative and renewable biofuel for blending with fossil-based diesel. One of the challenges is to design the supply-chain network for biohydrodeoxygenated diesel (BHD) under uncertainty from both raw materials availability and the demand. The supply chain with four echelons; suppliers, factories, inventories and customers has been studied. The biodiesel factory has been simulated by commercial simulation program Pro/II to find the utility cost and biodiesel production capacity. In this study, the stochastic optimization is used to solve mathematical model of the BHD supply chain network. The proposed model is based on stochastic mixed-integer programming with chance constraints. The chance constrained optimization has been applied to design supply chain network under the uncertainty at different levels of confidence. Then optimized supply chain network has been investigated on stability of the supply chain network under the uncertainties, accuracy of the profit and the effect of penalty. This study shows profit and trade-off between profit and penalty cost with different levels of confidence of BHD supply chain under uncertainties in raw-material supply and biodiesel demand. The results show that the chance constrained optimization can be used to design optimum supply chain network under uncertainties within levels of confidence.