A robust optimization model for a biofuel supply chain under demand uncertainty

The growing demand for fuels combined with the fact that there are limited fossil fuel resources has led the world to seek renewable energy resources such as biofuels. Micro-algae can be an efficient source of biofuel energy, since it significantly reduces air pollution. In this paper, we develop a micro-algae biofuel supply chain through a two-stage approach. This study aims to commercialize micro-algae as a new source of energy. In the first stage, we utilize the Best-Worst Method (BWM) to determine the best cultivation system, and in the second stage, a bi-objective mathematical model is presented which simultaneously optimizes the economic and environmental objectives. We also propose a robust optimization model to deal with the uncertain nature of the biofuel supply chain. Our analysis on the trade-off between the supply chain’s total cost and unfulfillment demand arrives at interesting managerial insights. Furthermore, to show the effectiveness of the robust optimization model, we compare the performance of the robust and deterministic models, and the results show that the robust model dominates over the deterministic model in all scenarios. Finally, sensitivity analysis on critical parameters is conducted to help decision-makers find the optimal trade-off between investment and its benefits.