Optimization-Based Approaches for Bioethanol Supply Chains

The E.U. has adopted a target of 10% of energy for transportation coming from renewable sources, including biofuels, by 2020 to tackle the increasing greenhouse gas emissions problem and reduce dependency on fossil fuels. In this paper, mixed integer linear programming (MLLP) models are presented for the optimal design of a bioethanol supply chain with the objective of minimizing the total supply chain cost. The models aim to optimize the locations and scales of the bioethanol production plants, biomass and bioethanol flows between regions, and the number of transport units required for the transfer of these products between regions as well as for local delivery. The optimal bioethanol production and biomass cultivation rates are also determined by the model. The applicability of the proposed models is demonstrated with a case study for Northern Italy.