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A mathematical model for microalgae-based biobutanol supply chain network design under harvesting and drying uncertainties

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  • Arabi, Mahsa
  • Yaghoubi, Saeed
  • Tajik, Javad

Abstract

Microalgae is one of the most promising feedstocks for biofuel production because it yields the high content of sugar and oil. In order to help to develop this nascent industry, this paper proposes a mixed integer linear programming (MILP) model for planning and designing a microalgae-based biobutanol supply chain network. The goal of this study is minimizing the fixed cost of constructing required facilities, transportation costs, and operational costs (harvesting, pretreatment, treatment, and energy conversion). This paper considers supply, production, distribution, and addresses a multi-period model. Since the volume of harvested and dried algae cannot be determined accurately, a fuzzy programming approach is employed to address uncertainties. Additionally, a data envelopment analysis (DEA) method is used to reduce the complexity of solving the proposed model. The applicability of the model is evaluated through a real case study of Iran.

Suggested Citation

  • Arabi, Mahsa & Yaghoubi, Saeed & Tajik, Javad, 2019. "A mathematical model for microalgae-based biobutanol supply chain network design under harvesting and drying uncertainties," Energy, Elsevier, vol. 179(C), pages 1004-1016.
    • Handle: RePEc:eee:energy:v:179:y:2019:i:c:p:1004-1016
    DOI: 10.1016/j.energy.2019.04.219
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    Cited by:

    1. Ravanipour, Masoumeh & Hamidi, Ali & Mahvi, Amir Hossein, 2021. "Microalgae biodiesel: A systematic review in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    2. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    3. Zeng, Jing & Wang, Zhenjun & Chen, Guobin, 2021. "Biological characteristics of energy conversion in carbon fixation by microalgae," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    4. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    5. Wang, Guotao & Liao, Qi & Wang, Chang & Liang, Yongtu & Zhang, Haoran, 2022. "Multiperiod optimal planning of biofuel refueling stations: A bi-level game-theoretic approach," Renewable Energy, Elsevier, vol. 200(C), pages 1152-1165.
    6. Olli-Jussi Korpinen & Mika Aalto & Raghu KC & Timo Tokola & Tapio Ranta, 2023. "Utilisation of Spatial Data in Energy Biomass Supply Chain Research—A Review," Energies, MDPI, vol. 16(2), pages 1-23, January.
    7. Naeini, Mina Alavi & Zandieh, Mostafa & Najafi, Seyyed Esmaeil & Sajadi, Seyed Mojtaba, 2020. "Analyzing the development of the third-generation biodiesel production from microalgae by a novel hybrid decision-making method: The case of Iran," Energy, Elsevier, vol. 195(C).
    8. Kang, Seongwhan & Heo, Seongmin & Realff, Matthew J. & Lee, Jay H., 2020. "Three-stage design of high-resolution microalgae-based biofuel supply chain using geographic information system," Applied Energy, Elsevier, vol. 265(C).

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