Sustainable Biofuel Supply Chain Planning and Management under Uncertainty

Abstract

The concept of environmental thinking is integrated into sustainable supply chain planning and management for biofuels, and a multiobjective modeling framework is developed. The aim is to seek best-compromise solutions that are economically and environmentally sustainable in supplying biofuels from cellulosic biomasses while satisfying demand, resource, and technology constraints. The least-cost objective and greenhouse gas (GHG) emissions reductions are integrated into the modeling framework, and carbon footprints are assessed with the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation model, a life-cycle assessment framework, to ensure that strategies to mitigate GHG emissions are factored into system planning and management. Biomass-to-biofuel conversion efficiency can be highly variable because of uncertainties inherent in the conversion processes; this uncertainty is considered explicitly in the integrated modeling framework. A multi-objective, mixed-integer, stochastic programming model is proposed and solved by the compromise method, a subclass of the goal programming method. The model is used to evaluate the economic potential and environmental impact of establishing a cellulosic ethanol supply chain based on biowaste (i.e., corn stover and forest residue) in California as a case study. Significant trade-offs exist between economic competitiveness and environmental quality. The uncertainty inherent in biomass-to-biofuel conversion technology has substantial effects on multicriteria decision making, and the effects may vary with the choice of modeling approaches.