a b s t r a c tThe production of biofuels, bioenergy and chemical intermediates from biomass is a promising solution to reduce the consumption of fossil fuels and greenhouse gas emissions. While a significant research effort has been devoted to biomass production and conversion processes, the importance of logistics was detected more recently. Indeed, efficient supply chains are essential to provide conversion facilities with sufficient quantities of quality biomass at reasonable prices. As large territories and hundreds of biomass producers are involved, quantitative models are very useful to evaluate and optimize the resources required, the associated costs, the energy consumptions and the environmental impacts. This article surveys the recent research on models for biomass supply chains, from an Operations Research perspective. 124 references, including 72 published since 2010, have been analyzed to present the structures and the activities of these chains, a typology of decisions in three levels (strategic, tactical and operational), and a review of models based either on performance evaluation techniques (e.g., simulation) or mathematical optimization. A conclusion underlines the contributions and shortcomings of current research and suggests possible directions.

The supply chains which bring biomass to biorefineries play a critical role in biofuel production. Optimization models can help decision makers to design more efficient chains and minimize the cost of biomass delivered to the refineries. This article based on a French national research project on biomass logistics considers one refinery, able to process several crops and several parts of the same crop, over a one-year horizon divided into days or weeks. A network model and a data model are first developed to let the decision maker describe the supply chain structure and its data, without affecting the underlying mathematical model. The latter is a mixed integer linear program which combines for the first time various features, either original or tackled separately in the literature. Knowing the refinery demands, it determines the activity levels in the network (amounts harvested, baled, transported, stored, etc.) and the required equipment, in order to minimize a total cost including harvesting costs, transport costs and storage costs. Numerical evaluations based on real data show that the proposed model can optimize large supply chains in reasonable running times.

The biorefineries of the future will critically depend on efficient supply chains to guarantee continuous flows of biomass while minimizing logistic costs and environmental impacts. OR techniques can be very useful to help decision makers to model, evaluate and optimize such complex and large-scale supply chains at the design stage. This paper provides an overview of the OR models for this recent research domain and proposes a core-model (mathematical program) for the tactical decision level.