An integrated MCDM – robust optimization framework for sustainable bioethanol supply chain design under uncertainty

Rapid industrialization worldwide, population growth, and the adverse environmental impacts of fossil fuel consumption have intensified interest in biofuel production. While biofuel production offers significant economic, environmental, and social benefits, it also poses challenges such as competition for natural resources, threats to food security, market instability, and increased pressure on water supplies. The use of second-generation biomass for biofuel production can mitigate many of these concerns. In this research, a novel two-stage framework is introduced for optimizing the bioethanol supply chain system design. In the initial stage, a multi-criteria decision-making technique is employed to rank biomass feedstocks to produce bioethanol, regarding economic, environmental, social, and technical factors. Consequently, in order to minimize the total network costs, while explicitly accounting for energy and water consumption, harmful gas emissions, land use, and food production, a multi-period optimization framework is created. The robust possibilistic programming approach is applied to confront the uncertain nature of the key inputs. The model is validated through an Iranian case study, with sensitivity analysis performed on key parameters. Numerical findings support the efficacy of the proposed model and demonstrate that production and transportation costs constitute the largest share of supply chain costs in both the certain and robust possibilistic models. The findings of the study also offer several practical insights related to bioethanol production and supply system for policymakers.