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Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach

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  • Azadeh, Ali
  • Vafa Arani, Hamed

Abstract

Development of biofuels causes reduction of environmental pollution, but certain limitations affect their production. In this research, a hybrid system dynamics-mathematical programming approach is developed to design and plan a biodiesel supply chain from biomass fields to consumption markets. The supply chain faces limitations in biodiesel production. Water resource limitations for biodiesel production, land limitations for biomass procurement, and technological issues are the most important limitations considered in the system dynamics model. In addition, competition between fossil fuels and biodiesel is taken into account. The proposed methodology, firstly, estimates the most important parameters in biodiesel supply chain in a given planning horizon. Then, estimated parameters are used as inputs of the mathematical model and the optimal supply chain decisions are made by means of a stochastic mixed-integer programming model. Besides, a scenario-based approach is used to model the disruption risks for links and biomass fields. Finally, a numerical experiment is presented to show the applicability of the methodology according to some interviews with experts in Iran. Results demonstrate the potential appropriate market of biodiesel in Iran while several resource and technology limitations and environmental pollution avoid growth of biodiesel market. Moreover, a sensitivity analysis is performed on risk preferences of decision makers and government policies adopted to improve the biodiesel market.

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  • Azadeh, Ali & Vafa Arani, Hamed, 2016. "Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach," Renewable Energy, Elsevier, vol. 93(C), pages 383-403.
    • Handle: RePEc:eee:renene:v:93:y:2016:i:c:p:383-403
    DOI: 10.1016/j.renene.2016.02.070
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    1. Huang, Yongxi & Chen, Chien-Wei & Fan, Yueyue, 2010. "Multistage optimization of the supply chains of biofuels," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 820-830, November.
    2. Jeffers, Robert F. & Jacobson, Jacob J. & Searcy, Erin M., 2013. "Dynamic analysis of policy drivers for bioenergy commodity markets," Energy Policy, Elsevier, vol. 52(C), pages 249-263.
    3. Awudu, Iddrisu & Zhang, Jun, 2012. "Uncertainties and sustainability concepts in biofuel supply chain management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1359-1368.
    4. Jeroen Struben & John D Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Environment and Planning B, , vol. 35(6), pages 1070-1097, December.
    5. Giarola, Sara & Zamboni, Andrea & Bezzo, Fabrizio, 2012. "Environmentally conscious capacity planning and technology selection for bioethanol supply chains," Renewable Energy, Elsevier, vol. 43(C), pages 61-72.
    6. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    7. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    8. Avami, Akram, 2013. "Assessment of optimal biofuel supply chain planning in Iran: Technical, economic, and agricultural perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 761-768.
    9. Shabani, Nazanin & Sowlati, Taraneh, 2013. "A mixed integer non-linear programming model for tactical value chain optimization of a wood biomass power plant," Applied Energy, Elsevier, vol. 104(C), pages 353-361.
    10. Amigun, B. & Musango, J.K. & Brent, A.C., 2011. "Community perspectives on the introduction of biodiesel production in the Eastern Cape Province of South Africa," Energy, Elsevier, vol. 36(5), pages 2502-2508.
    11. Awudu, Iddrisu & Zhang, Jun, 2013. "Stochastic production planning for a biofuel supply chain under demand and price uncertainties," Applied Energy, Elsevier, vol. 103(C), pages 189-196.
    12. Zhang, Fengli & Johnson, Dana M. & Johnson, Mark A., 2012. "Development of a simulation model of biomass supply chain for biofuel production," Renewable Energy, Elsevier, vol. 44(C), pages 380-391.
    13. Musango, Josephine K. & Brent, Alan C. & Amigun, Bamikole & Pretorius, Leon & Müller, Hans, 2011. "Technology sustainability assessment of biodiesel development in South Africa: A system dynamics approach," Energy, Elsevier, vol. 36(12), pages 6922-6940.
    14. Grigoroudis, Evangelos & Petridis, Konstantinos & Arabatzis, Garyfallos, 2014. "RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks," Renewable Energy, Elsevier, vol. 71(C), pages 113-122.
    15. Jeroen Struben & John D. Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Post-Print hal-02312277, HAL.
    16. Zhang, Jun & Osmani, Atif & Awudu, Iddrisu & Gonela, Vinay, 2013. "An integrated optimization model for switchgrass-based bioethanol supply chain," Applied Energy, Elsevier, vol. 102(C), pages 1205-1217.
    17. Papapostolou, Christiana & Kondili, Emilia & Kaldellis, John K., 2011. "Development and implementation of an optimisation model for biofuels supply chain," Energy, Elsevier, vol. 36(10), pages 6019-6026.
    18. van Dyken, Silke & Bakken, Bjorn H. & Skjelbred, Hans I., 2010. "Linear mixed-integer models for biomass supply chains with transport, storage and processing," Energy, Elsevier, vol. 35(3), pages 1338-1350.
    19. Azadeh, Ali & Vafa Arani, Hamed & Dashti, Hossein, 2014. "A stochastic programming approach towards optimization of biofuel supply chain," Energy, Elsevier, vol. 76(C), pages 513-525.
    20. Schmidt, Johannes & Leduc, Sylvain & Dotzauer, Erik & Schmid, Erwin, 2011. "Cost-effective policy instruments for greenhouse gas emission reduction and fossil fuel substitution through bioenergy production in Austria," Energy Policy, Elsevier, vol. 39(6), pages 3261-3280, June.
    21. Glenn Pederson & Tianyu Zou, 2009. "Using real options to evaluate ethanol plant expansion decisions," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 69(1), pages 23-35, May.
    22. Pereira, Roberto G. & Oliveira, Cesar D. & Oliveira, Jorge L. & Oliveira, Paulo Cesar P. & Fellows, Carlos E. & Piamba, Oscar E., 2007. "Exhaust emissions and electric energy generation in a stationary engine using blends of diesel and soybean biodiesel," Renewable Energy, Elsevier, vol. 32(14), pages 2453-2460.
    23. Aslani, Alireza & Helo, Petri & Feng, Bo & Antila, Erkki & Hiltunen, Erkki, 2013. "Renewable energy supply chain in Ostrobothnia region and Vaasa city: Innovative framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 405-411.
    24. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
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    2. Ghadge, Abhijeet & van der Werf, Sjoerd & Er Kara, Merve & Goswami, Mohit & Kumar, Pankaj & Bourlakis, Michael, 2020. "Modelling the impact of climate change risk on bioethanol supply chains," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    3. Shohre Khoddami & Fereshteh Mafakheri & Yong Zeng, 2021. "A System Dynamics Approach to Comparative Analysis of Biomass Supply Chain Coordination Strategies," Energies, MDPI, vol. 14(10), pages 1-35, May.
    4. Chávez, Marcela María Morales & Sarache, William & Costa, Yasel, 2018. "Towards a comprehensive model of a biofuel supply chain optimization from coffee crop residues," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 136-162.
    5. Hasan, Atiye Haj & Avami, Akram, 2018. "Water and emissions nexus for biodiesel in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 354-363.
    6. Eirini Aivazidou & Dimitrios Aidonis & Naoum Tsolakis & Charisios Achillas & Dimitrios Vlachos, 2022. "Wine Supply Chain Network Configuration under a Water Footprint Cap," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    7. Ramos-Hernández, Rocío & Sánchez-Ramírez, Cuauhtémoc & Mota-López, Dulce Rocio & Sandoval-Salas, Fabiola & García-Alcaraz, Jorge Luis, 2021. "Evaluation of bioenergy potential from coffee pulp trough System Dynamics," Renewable Energy, Elsevier, vol. 165(P1), pages 863-877.

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