TY - JOUR
T1 - Integrated strategic and tactical biomass-biofuel supply chain optimization
AU - Lin, Tao
AU - Rodríguez, Luis F.
AU - Shastri, Yogendra N.
AU - Hansen, Alan C.
AU - Ting, K. C.
N1 - Funding Information:
The study is funded by the Energy Biosciences Institute through the program titled “Engineering Solutions for Biomass Feedstock Production”. The authors would like to acknowledge the detailed and helpful comments from the editor and two anonymous reviewers to the manuscript.
PY - 2014/3
Y1 - 2014/3
N2 - To ensure effective biomass feedstock provision for large-scale biofuel production, an integrated biomass supply chain optimization model was developed to minimize annual biomass-ethanol production costs by optimizing both strategic and tactical planning decisions simultaneously. The mixed integer linear programming model optimizes the activities range from biomass harvesting, packing, in-field transportation, stacking, transportation, preprocessing, and storage, to ethanol production and distribution. The numbers, locations, and capacities of facilities as well as biomass and ethanol distribution patterns are key strategic decisions; while biomass production, delivery, and operating schedules and inventory monitoring are key tactical decisions. The model was implemented to study Miscanthus-ethanol supply chain in Illinois. The base case results showed unit Miscanthus-ethanol production costs were $0.72L>sup>-1>/sup> of ethanol. Biorefinery related costs accounts for 62% of the total costs, followed by biomass procurement costs. Sensitivity analysis showed that a 50% reduction in biomass yield would increase unit production costs by 11%.
AB - To ensure effective biomass feedstock provision for large-scale biofuel production, an integrated biomass supply chain optimization model was developed to minimize annual biomass-ethanol production costs by optimizing both strategic and tactical planning decisions simultaneously. The mixed integer linear programming model optimizes the activities range from biomass harvesting, packing, in-field transportation, stacking, transportation, preprocessing, and storage, to ethanol production and distribution. The numbers, locations, and capacities of facilities as well as biomass and ethanol distribution patterns are key strategic decisions; while biomass production, delivery, and operating schedules and inventory monitoring are key tactical decisions. The model was implemented to study Miscanthus-ethanol supply chain in Illinois. The base case results showed unit Miscanthus-ethanol production costs were $0.72L>sup>-1>/sup> of ethanol. Biorefinery related costs accounts for 62% of the total costs, followed by biomass procurement costs. Sensitivity analysis showed that a 50% reduction in biomass yield would increase unit production costs by 11%.
KW - Biofuel
KW - Biomass
KW - Cost
KW - Optimization
KW - Supply chain
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U2 - 10.1016/j.biortech.2013.12.121
DO - 10.1016/j.biortech.2013.12.121
M3 - Article
C2 - 24508904
AN - SCOPUS:84893447511
SN - 0960-8524
VL - 156
SP - 256
EP - 266
JO - Bioresource Technology
JF - Bioresource Technology
ER -