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              computing techniques are needed, as well as more data and standardi-
              zation on selecting and documenting different methodological options.
          (3) The conflicts and relationships between stakeholders at varied scales and
              levels in BSC need a better understanding to support effective BSC
              design at an early stage.
          (4) In addition to optimization, which has been widely used in BSC design,
              other modeling tools such as ABM and GIS demonstrate a strong capa-
              bility in supporting BSC decision-making. More case studies will be
              needed to explore the broader use and effectiveness of different model-
              ing techniques for BSC design.



          References

          Aden, A., Ruth, M., Ibsen, K., Jechura, J., Neeves, K., Sheehan, J., Wallace, B.,
             Montague, L., Slayton, A., Lukas, J., 2002. Lignocellulosic Biomass to Ethanol Process
             Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic
             Hydrolysis for Corn Stover (No. NREL/TP-510-32438). U.S. NationalRenewable
             Energy Laboratory, Golden, Colorado, pp. 181–189.
          Agusdinata, D.B., Lee, S., Zhao, F., Thissen, W., 2014. Simulation modeling framework for
             uncovering system behaviors in the biofuels supply chain network. Simulation 90 (9),
             1103–1116.
          Akgul, O., Shah, N., Papageorgiou, L.G., 2012a. An optimisation framework for a hybrid
             first/second generation bioethanol supply chain. Comput. Chem. Eng. 42, 101–114.
          Akgul, O., Shah, N., Papageorgiou, L.G., 2012b. Economic optimisation of a UK advanced
             biofuel supply chain. Biomass Bioenergy 41, 57–72.
          Alex Marvin, W., Schmidt, L.D., Benjaafar, S., Tiffany, D.G., Daoutidis, P., 2012. Eco-
             nomic optimization of a lignocellulosic biomass-to-ethanol supply chain. Chem. Eng.
             Sci. 67 (1), 68–79.
          Alleman, T.L., McCormick, R.L., Christensen, E.D., Fioroni, G., Moriarty, K.,
             Yanowitz, J., 2016. Biodiesel Handling and Use Guide (No. NREL/BK-5400-
             66521; DOE/GO-102016-4875).
          An, H., Wilhelm, W.E., Searcy, S.W., 2011a. Biofuel and petroleum-based fuel supply chain
             research: a literature review. Biomass Bioenergy 35 (9), 3763–3774.
          An, H., Wilhelm, W.E., Searcy, S.W., 2011b. A mathematical model to design a lignocel-
             lulosic biofuel supply chain system with a case study based on a region in central texas.
             Bioresour. Technol. 102 (17), 7860–7870.
          Avami, A., 2013. Assessment of optimal biofuel supply chain planning in iran: technical, eco-
             nomic, and agricultural perspectives. Renew. Sust. Energ. Rev. 26, 761–768.
          Awudu, I., Zhang, J., 2012. Uncertainties and sustainability concepts in biofuel supply chain
             management: a review. Renew. Sust. Energ. Rev. 16 (2), 1359–1368.
          Awudu, I., Zhang, J., 2013. Stochastic production planning for a biofuel supply chain under
             demand and price uncertainties. Appl. Energy 103, 189–196.
          Ayoub, N., Elmoshi, E., Seki, H., Naka, Y., 2009. Evolutionary algorithms approach for
             integrated bioenergy supply chains optimization. Energy Convers. Manag. 50 (12),
             2944–2955.
          Azadeh, A., Vafa Arani, H., Dashti, H., 2014. A stochastic programming approach towards
             optimization of biofuel supply chain. Energy 76, 513–525.
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