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Sustainable supply chain planning for biomass-based power generation with environmental risk and supply uncertainty considerations: a real-life case study

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  • Mohammad Fattahi
  • Kannan Govindan
  • Mehdi Farhadkhani

Abstract

This paper addresses the design and planning of a supply chain (SC) system for power generation from biomass by using various technologies. A two-stage stochastic programming model is developed to find an effective design strategy under stochastic and highly seasonal biomass supply. The biomass usage, as a renewable energy source, for the power generation affects the environment and society in multiple ways, such as social expectations, life-threatening issues, and greenhouse gas emissions. As a consequence, in the stochastic model, by the social life cycle assessment (S-LCA) approach, the SC’s social impact is guaranteed to be larger than a minimum acceptable rate. Furthermore, the environmental risk of the SC is quantified based on its air pollutant and greenhouse gas emissions and mitigated. To deal with the biomass supply uncertainty, discrete scenarios are generated using a backward scenario reduction approach. Computational results are presented on a real-life case study in Iran to show the stochastic model’s applicability in evaluating the economic potential, the sustainability aspects, and the required infrastructure for the planning of the SC system. In addition, to drive managerial insights, sensitivity analysis on key parameters of the optimisation problem is done.

Suggested Citation

  • Mohammad Fattahi & Kannan Govindan & Mehdi Farhadkhani, 2021. "Sustainable supply chain planning for biomass-based power generation with environmental risk and supply uncertainty considerations: a real-life case study," International Journal of Production Research, Taylor & Francis Journals, vol. 59(10), pages 3084-3108, May.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:10:p:3084-3108
    DOI: 10.1080/00207543.2020.1746427
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    Cited by:

    1. Bahmani, Pardis & Dehghani Sadrabadi, Mohammad Hossein & Makui, Ahmad & Jafari-Nodoushan, Abbasali, 2024. "An optimization-based design methodology to manage the sustainable biomass-to-biodiesel supply chain under disruptions: A case study," Renewable Energy, Elsevier, vol. 229(C).
    2. Jamalnia, Aboozar & Gong, Yu & Govindan, Kannan, 2023. "Sub-supplier's sustainability management in multi-tier supply chains: A systematic literature review on the contingency variables, and a conceptual framework," International Journal of Production Economics, Elsevier, vol. 255(C).
    3. Edgar Gutierrez-Franco & Andres Polo & Nicolas Clavijo-Buritica & Luis Rabelo, 2021. "Multi-Objective Optimization to Support the Design of a Sustainable Supply Chain for the Generation of Biofuels from Forest Waste," Sustainability, MDPI, vol. 13(14), pages 1-27, July.
    4. Santibañez-Aguilar, José Ezequiel & Quiroz-Ramírez, Juan José & Sánchez-Ramírez, Eduardo & Segovia-Hernández, Juan Gabriel & Flores-Tlacuahuac, Antonio & Ponce-Ortega, José María, 2022. "Marginalization index as social measure for Acetone-Butanol-Ethanol supply chain planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    5. Islam Hassanin & Matjaz Knez, 2022. "Managing Supply Chain Activities in the Field of Energy Production Focusing on Renewables," Sustainability, MDPI, vol. 14(12), pages 1-33, June.
    6. Sadeghi Darvazeh, Saeed & Mansoori Mooseloo, Farzaneh & Gholian-Jouybari, Fatemeh & Amiri, Maghsoud & Bonakdari, Hossein & Hajiaghaei-Keshteli, Mostafa, 2024. "Data-driven robust optimization to design an integrated sustainable forest biomass-to-electricity network under disjunctive uncertainties," Applied Energy, Elsevier, vol. 356(C).
    7. Seyed Mojib Zahraee & Nirajan Shiwakoti & Peter Stasinopoulos, 2024. "Metaheuristic Optimization of the Agricultural Biomass Supply Chain: Integrating Strategic, Tactical, and Operational Planning," Energies, MDPI, vol. 17(16), pages 1-35, August.
    8. Hmouda, Ahmed M.O. & Orzes, Guido & Sauer, Philipp C., 2024. "Sustainable supply chain management in energy production: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    9. Yunusoglu, Pinar & Ozsoydan, Fehmi Burcin & Bilgen, Bilge, 2024. "A machine learning-based two-stage approach for the location of undesirable facilities in the biomass-to-bioenergy supply chain," Applied Energy, Elsevier, vol. 362(C).
    10. Zhang, Shuai & Lei, Qingyu & Wu, Le & Wang, Yuqi & Zheng, Lan & Chen, Xi, 2022. "Supply chain design and integration for the Co-Processing of bio-oil and vacuum gas oil in a refinery," Energy, Elsevier, vol. 241(C).

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