Multiobjective Robust Possibilistic Programming Approach to Sustainable Bioethanol Supply Chain Design under Multiple Uncertainties

In this article, a multiobjective mixed-integer linear programming (MILP) model is proposed to address the optimal design and planning of a lignocellulosic bioethanol supply chain (LBSC) considering a sustainable supply chain optimization framework including economic, environmental, and social objectives. The proposed model is capable of determining strategic decisions, including biomass sourcing and allocation, locations, capacity levels, and technology types of biorefinery facilities, as well as the tactical decisions, including inventory levels, production amounts, and shipments among the network. Eco-indicator 99, which is a well-known life-cycle-assessment- (LCA-) based environmental impact assessment method, is incorporated into the model to estimate the relevant environmental impacts. To handle the inherent uncertainty of the input data in the problem of interest, a novel multiobjective robust possibilistic programming (MORPP) approach is developed. The performance of the model is demonstrated through a case study developed for a biofuel supply chain in Iran. Diverse solutions achieved by the proposed MORPP approach outperform deterministic solutions in terms of given performance measures.