Free Access
Issue
RAIRO-Oper. Res.
Volume 55, 2021
Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
Page(s) S2653 - S2675
DOI https://doi.org/10.1051/ro/2020104
Published online 02 March 2021
  • H. An, W.E. Wilhelm and S.W. Searcy, A mathematical model to design a lignocellulosic biofuel supply chain system with a case study based on a region in Central Texas. Bioresour. Technol. 102 (2011) 7860–7870. [Google Scholar]
  • A. Azadeh, H.V. Arani and H. Dashti, A stochastic programming approach towards optimization of biofuel supply chain. Energy 76 (2014) 513–525. [CrossRef] [Google Scholar]
  • R. Babazadeh, J. Razmi, M.S. Pishvaee and M. Rabbani, A non-radial DEA model for location optimization of Jatropha curcas L. Cultivation. Ind. Crops Prod. 69 (2015) 197–203. [Google Scholar]
  • Ș.Y. Balaman and H. Selim, A network design model for biomass to energy supply chains with anaerobic digestion systems. Appl. Energy 130 (2014) 289–304. [Google Scholar]
  • Ș.Y. Balaman and H. Selim, A fuzzy multiobjective linear programming model for design and management of anaerobic digestion based bioenergy supply chains. Energy 74 (2014) 928–940. [Google Scholar]
  • G. Corsano, A.R. Vecchietti and J.M. Montagna, Optimal design for sustainable bioethanol supply chain considering detailed plant performance model. Comput. Chem. Eng. 35 (2011) 1384–1398. [Google Scholar]
  • G. Corsano, Y. Fumero and J.M. Montagna, Integrated decision making for the optimal bioethanol supply chain. Energy Convers. Manage. 88 (2014) 1127–1742. [Google Scholar]
  • M.G. Doggar, M. Shahzad Khurram, S. Mirza, M. Ghauri, F. Jamil, N. Muhammad, S. Rafiq and M.H. Jaffery, Biomass power generation potential and utlization in pakistan. Curr. Org. Chem. 22 (2018) 1–16. [Google Scholar]
  • J.R. Doyle and R.H. Green, Efficiency and cross-efficiency in DEA derivations, meanings and uses. J. Oper. Res. Soc. 45 (1994) 567–578. [Google Scholar]
  • L.S. Ferreira and J.O. Trierweiler, Modeling and simulation of the polymeric nanocapsule formation process. IFAC Proc. 42 (2009) 405–410. [Google Scholar]
  • V. Gonela, J. Zhang and A. Osmani, Stochastic optimization of sustainable industrial symbiosis based hybrid generation bioethanol supply chains. Comput. Ind. Eng. 87 (2015) 40–65. [Google Scholar]
  • K. Grzesik and M. Malinowski, Life cycle assessment of mechanical–biological treatment of mixed municipal waste.Environ. Eng. Sci. 34 (2017) 207–220. [Google Scholar]
  • Y. Gu and B.K. Wylie, Using satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA. Ecol. Indic. 60 (2016) 64–70. [Google Scholar]
  • R. Kesharwani, Z. Sun and C. Dagli, Biofuel supply chain optimal design considering economic, environmental, and societal aspects towards sustainability. Int. J. Energy Res. 42 (2018) 2169–2198. [Google Scholar]
  • F. Mafakheri and F. Nasiri, Modeling of biomass-to-energy supply chain operations: applications, challenges and research directions. Energy Policy 67 (2014) 116–126. [Google Scholar]
  • M. Marufuzzaman, S.D. Eksioglu, X. Li and J. Wang, Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain. Transp. Res. Part E: Logistics Transp. Rev. 69 (2014) 122–145. [Google Scholar]
  • W.A. Marvin, L.D. Schmidt and P. Daoutidis, Biorefinery location and technology selection through supply chain optimization. Ind. Eng. Chem. Res. 52 (2012) 3192–3208. [Google Scholar]
  • S. Mohseni and M.S. Pishvaee, A robust programming approach towards design and optimization of microalgae-based biofuel supply chain. Comput. Ind. Eng. 100 (2016) 58–71. [Google Scholar]
  • S. Mohseni, M.S. Pishvaee and H. Sahebi, Robust design and planning of microalgae biomass-to-biodiesel supply chain: a case study in Iran. Energy 111 (2016) 736–755. [CrossRef] [Google Scholar]
  • M. Moulod, A. Jalali and R. Asmatulu, Biogas derived from municipal solid waste to generate electrical power through solid oxide fuel cells. Int. J. Energy Res. 40 (2016) 2091–2104. [Google Scholar]
  • R.T. Ng and C.T. Maravelias, Design of cellulosic ethanol supply chains with regional depots. Ind. Eng. Chem. Res. 55 (2015) 3420–3432. [Google Scholar]
  • A. Osmani and J. Zhang, Economic and environmental optimization of a large scale sustainable dual feedstock lignocellulosic-based bioethanol supply chain in a stochastic environment. Appl. Energy 114 (2014) 572–587. [Google Scholar]
  • A. Osmani and J. Zhang, Multi-period stochastic optimization of a sustainable multi-feedstock second generation bioethanol supply chain – A logistic case study in Midwestern United States. Land Use Policy. 61 (2017) 420–450. [Google Scholar]
  • M. Patel, X. Zhang and A. Kumar, Techno-economic and life cycle assessment on lignocellulosic biomass thermochemical conversion technologies: a review. Renew. Sustainable Energy Rev. 53 (2016) 1486–1499. [Google Scholar]
  • S.R. Poudel, M. Marufuzzaman and L. Bian, Designing a reliable bio-fuel supply chain network considering link failure probabilities. Comput. Ind. Eng. 91 (2016) 85–99. [Google Scholar]
  • S. Rafael, L. Tarelho, A. Monteiro, T. Monteiro, C. Gonçalves, S. Freitas and M. Lopes, Atmospheric emissions from forest biomass residues to energy supply chain: a case study in Portugal. Environ. Eng. Sci. 32 (2015) 505–515. [Google Scholar]
  • G.J. Ruiz-Mercado, M.A. Gonzalez and R.L. Smith, Sustainability indicators for chemical processes: III. Biodiesel case study. Ind. Eng. Chem. Res. 52 (2013) 6747–6760. [Google Scholar]
  • J. Sadhukhan and K.S. Ng, Economic and European union environmental sustainability criteria assesment of bio-oil-based biofuel systems: refinery integration cases. Ind. Eng. Chem. Res. 50 (2011) 6794–6808. [Google Scholar]
  • H. Sahebi, S. Nickel and J. Ashayeri, Strategic and tactical mathematical programming models within the crude oil supply chain context – A review. Comput. Chem. Eng. 68 (2014) 56–77. [Google Scholar]
  • N. Shabani, T. Sowlati, M. Ouhimmou and M. Rönnqvist, Tactical supply chain planning for a forest biomass power plant under supply uncertainty. Energy 78 (2014) 346–355. [Google Scholar]
  • B. Sharma, R.G. Ingalls, C.L. Jones and A. Khanchi, Biomass supply chain design and analysis: basis, overview, modeling, challenges, and future. Renew. Sustainable Energy Rev. 24 (2013) 608–27. [Google Scholar]
  • B. Sharma, R.G. Ingalls, C.L. Jones, R.L. Huhnke and A. Khanchi, Scenario optimization modeling approach for design and management of biomass-to-bio-refinery supply chain system. Bioresour. Technol. 150 (2013) 163–171. [Google Scholar]
  • X. Wang, G. Huang, Z. Liu and C. Dai, Hybrid inexact optimization approach with data envelopment analysis for environment management and planning in the city of Beijing, China. Environ. Eng. Sci. 29 (2012) 313–327. [Google Scholar]
  • L. Wang, M. Sharifzadeh, R. Templer and R.J. Murphy, Bioethanol production from various waste papers: economic feasibility and sensitivity analysis. Appl. Energy 111 (2013) 1172–1782. [Google Scholar]
  • F. Xie, Y. Huang and S. Eksioglu, Integrating multimodal transport into cellulosic biofuel supply chain design under feedstock seasonality with a case study based on California. Bioresour. Technol. 152 (2014) 15–23. [Google Scholar]
  • H. Zhou, Y. Yang, Y. Chen and J. Zhu, Data envelopment analysis application in sustainability: the origins, development and future directions. Eur. J. Oper. Res. 264 (2018) 1–16. [Google Scholar]

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