Developing a sustainable supply chain optimization model for switchgrass-based bioenergy production: A case study

Abstract

Renewable energies are attracting considerable interest as an appropriate alternative for the fossil fuel-based sources of energy due to increasing concerns about global warming and environmental issues. In this regard, this paper takes a new look at designing a sustainable Switchgrass-based bioenergy supply chain network (BSCN) incorporating conflicting economic, environmental and social objectives. We propose a novel, multi-objective, mixed integer linear programming model as a decision-making (DM) tool. To deal with sustainability factors, the proposed model is solved using two-stage algorithms consisting of augmented ε-constraint and TOPSIS. This approach paves the way to determine the suitable strategical and tactical decisions and manage bioenergy supply chain performance with respect to the preference of decision makers for appropriate trade-off among of the sustainability factors. Computational analysis is carried out to indicate the validity of the proposed model by using a real case study in Iran. The results demonstrate that achieving a desirable level of social and environmental preservation conducted a circa 15% increase in economic objective function at the end of planning horizon. The results also show that high investment cost is a precondition to improving BSCN. It behooves the government to prioritize their plans and compartmentalize their budgets and spending in more constructive and effective ways related to bioenergy supply chain planning.