Annals of Operations Research https://doi.org/10.1007/s10479-019-03477-8 S.I.: AGRICULTURE ANALYTICS, BIGDATA AND SUSTAINABLE DEVELOPMENT Modeling and optimization of biomass quality variability for decision support systems in biomass supply chains Mario Aboytes-Ojeda 1 · Krystel K. Castillo-Villar 1 · Sandra D. Eksioglu 2 © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract A feasible alternative to the production of fossil fuels is the production of biofuels. In order to minimize the costs of producing biofuels, we developed a stochastic programming for- mulation that optimizes the inbound delivery of biomass. The proposed model captures the variability in the moisture and ash content in the biomass, which define its quality and affect the cost of biofuel. We propose a novel hub-and-spoke network to take advantage of the economies of scale in transportation and to minimize the effect of poor quality. The first- stage variables are the potential locations of depots and biorefineries, and the necessary unit trains to transport the biomass. The second-stage variables are the flow of biomass between the network nodes and the third-party bioethanol supply. A case study from Texas is presented. The numerical results show that the biomass quality changes the selected depot/biorefinery locations and conversion technology in the optimal network design. The cost due to poor biomass quality accounts for approximately 8.31% of the investment and operational cost. Our proposed L-shaped with connectivity constraints approach outperforms the benchmark L-shaped method in terms of solution quality and computational effort by 0.6% and 91.63% on average, respectively. Keywords Biofuels · Biomass · Optimization · Stochastic programming · Two-stage problems · L-shaped method B Krystel K. Castillo-Villar Krystel.Castillo@utsa.edu Mario Aboytes-Ojeda aboalfa80@yahoo.com.edu Sandra D. Eksioglu seksiog@clemson.edu 1 Texas Sustainable Energy Research Institute and Mechanical Engineering Department, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA 2 Department of Industrial Engineering, Clemson University, 277-C Freeman Hall, Clemson, SC 29634, USA 123