A robust optimization approach for an integrated hybrid biodiesel and biomethane supply chain network design under uncertainty: case study

To overcome the problems of environmental concerns and the depletion of fossil resources, as well as to improve energy security, renewable energy resources can be substituted for petroleum-based fuels. Transportation sector can benefit from the utilization of biodiesel and biomethane as suitable green fuels. This study proposes a multi-period mixed-integer linear programming model to manage and design the biofuel supply chain network from two high-potential energy crops. This novel two-stage stochastic programming model aims to minimize overall cost as well as the environmental impacts of transportation and biofuel production. To manage the uncertainty in the biofuel supply chain network, a robust optimization approach is applied to hedge against demand uncertainty. To deal with the bi-objective programming model, an interactive fuzzy approach is employed. The usefulness of the model is illustrated by a real case study in Iran. Finally, the computational results are evaluated and discussed. Furthermore, a sensitivity analysis is performed on parameters that address decision-makers’ preferences and environmental concerns in the biofuel production system.