Page 357 - Biofuels for a More Sustainable Future
P. 357
Key issue, challenges, and status quo of models for biofuel supply chain design 313
Ravula, P.P., Grisso, R.D., Cundiff, J.S., 2008. Comparison between two policy strategies for
scheduling trucks in a biomass logistic system. Bioresour. Technol. 99 (13), 5710–5721.
Ren, J., Dong, L., Sun, L., Goodsite, M.E., Tan, S., Dong, L., 2015. Life cycle cost opti-
mization of biofuel supply chains under uncertainties based on interval linear program-
ming. Bioresour. Technol. 187, 6–13.
Rentizelas, A.A., Tolis, A.J., Tatsiopoulos, I.P., 2009a. Logistics issues of biomass: the storage
problem and the multi-biomass supply chain. Renew. Sust. Energ. Rev. 13 (4), 887–894.
Rentizelas, A.A., Tatsiopoulos, I.P., Tolis, A., 2009b. An optimization model for multi-
biomass tri-generation energy supply. Biomass Bioenergy 33 (2), 223–233.
Rickman, D.S., Schwer, R.K., 1995. A comparison of the multipliers of IMPLAN, REMI,
and RIMS II: benchmarking ready-made models for comparison. Ann. Reg. Sci. 29 (4),
363–374.
Rinco ´n, L.E., Valencia, M.J., Herna ´ndez, V., Matallana, L.G., Cardona, C.A., 2015. Opti-
mization of the Colombian biodiesel supply chain from oil palm crop based on techno-
economical and environmental criteria. Energy Econ. 47, 154–167.
Ringer, M., Ringer, M., Putsche, V., Putsche, V., Scahill, J., Scahill, J., 2006. Large-Scale
Pyrolysis Oil Production: A Technology Assessment and Economic Analysis. National
Renewable Energy Lab (NREL), Golden, CO, USA.
Romano, R.T., Zhang, R., 2008. Co-digestion of onion juice and wastewater sludge using
an anaerobic mixed biofilm reactor. Bioresour. Technol. 99 (3), 631–637.
Roubens, M., Teghem, J., 1991. Comparison of methodologies for fuzzy and stochastic
multi-objective programming. Fuzzy Sets Syst. 42 (1), 119–132.
Sammons Jr., N., Eden, M., Yuan, W., Cullinan, H., Aksoy, B., 2007. A flexible framework
for optimal biorefinery product allocation. Environ. Prog. 26 (4), 349–354.
Sammons, N.E., Yuan, W., Eden, M.R., Aksoy, B., Cullinan, H.T., 2008. Optimal bior-
efinery product allocation by combining process and economic modeling. Chem.
Eng. Res. Des. 86 (7), 800–808.
Santiban ˜ez-Aguilar, J.E., Gonza ´lez-Campos, J.B., Ponce-Ortega, J.M., Serna-Gonza ´lez, M.,
El-Halwagi, M.M., 2014. Optimal planning and site selection for distributed multipro-
duct biorefineries involving economic, environmental and social objectives. J. Clean.
Prod. 65, 270–294.
Santiban ˜ez-Aguilar, J.E., Morales-Rodriguez, R., Gonza ´lez-Campos, J.B., Ponce-
Ortega, J.M., 2016. Stochastic design of biorefinery supply chains considering economic
and environmental objectives. J. Clean. Prod. 136, 224–245.
Santoso, T., Ahmed, S., Goetschalckx, M., Shapiro, A., 2005. A stochastic programming
approach for supply chain network design under uncertainty. Eur. J. Oper. Res.
167 (1), 96–115.
Scheffran, J., BenDor, T., 2009. Bioenergy and land use: a spatial-agent dynamic model of
energy crop production in Illinois. Int. J. Environ. Pollut. 39 (1/2), 4.
Sharma, B., Ingalls, R.G., Jones, C.L., Khanchi, A., 2013. Biomass supply chain design and
analysis: basis, overview, modeling, challenges, and future. Renew. Sust. Energ. Rev.
24, 608–627.
Shastri, Y., Rodrı ´guez, L., Hansen, A., Ting, K.C., 2011. Agent-based analysis of biomass
feedstock production dynamics. Bioenergy Res. 4 (4), 258–275.
Sims, R.E.H., Venturi, P., 2004. All-year-round harvesting of short rotation coppice euca-
lyptus compared with the delivered costs of biomass from more conventional short sea-
son, harvesting systems. Biomass Bioenergy 26 (1), 27–37.
Sims, R.E.H., Mabee, W., Saddler, J.N., Taylor, M., 2010. An overview of second gener-
ation biofuel technologies. Bioresour. Technol. 101 (6), 1570–1580.
Singh, A., Pant, D., Korres, N.E., Nizami, A.S., Prasad, S., Murphy, J.D., 2010. Key issues in
life cycle assessment of ethanol production from lignocellulosic biomass: challenges and
perspectives. Bioresour. Technol. 101 (13), 5003–5012.

