IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v179y2019icp1004-1016.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421930859X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.04.219?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    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. Lidia Angulo-Meza & Marcos Lins, 2002. "Review of Methods for Increasing Discrimination in Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 116(1), pages 225-242, October.
    5. Kornbluth, Jonathan S. H. & Steuer, Ralph E., 1981. "Goal programming with linear fractional criteria," European Journal of Operational Research, Elsevier, vol. 8(1), pages 58-65, September.
    6. Zhang, Fengli & Johnson, Dana M. & Wang, Jinjiang, 2016. "Integrating multimodal transport into forest-delivered biofuel supply chain design," Renewable Energy, Elsevier, vol. 93(C), pages 58-67.
    7. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    8. 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.
    9. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    10. Chen, Chien-Wei & Fan, Yueyue, 2012. "Bioethanol supply chain system planning under supply and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 150-164.
    11. 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.
    12. 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.
    13. Ghelichi, Zabih & Saidi-Mehrabad, Mohammad & Pishvaee, Mir Saman, 2018. "A stochastic programming approach toward optimal design and planning of an integrated green biodiesel supply chain network under uncertainty: A case study," Energy, Elsevier, vol. 156(C), pages 661-687.
    14. Zhang, Fengli & Johnson, Dana & Johnson, Mark & Watkins, David & Froese, Robert & Wang, Jinjiang, 2016. "Decision support system integrating GIS with simulation and optimisation for a biofuel supply chain," Renewable Energy, Elsevier, vol. 85(C), pages 740-748.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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).
    7. 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.
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    2. 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.
    3. He-Lambert, Lixia & English, Burton C. & Lambert, Dayton M. & Shylo, Oleg & Larson, James A. & Yu, T. Edward & Wilson, Bradly, 2018. "Determining a geographic high resolution supply chain network for a large scale biofuel industry," Applied Energy, Elsevier, vol. 218(C), pages 266-281.
    4. Mafakheri, Fereshteh & Nasiri, Fuzhan, 2014. "Modeling of biomass-to-energy supply chain operations: Applications, challenges and research directions," Energy Policy, Elsevier, vol. 67(C), pages 116-126.
    5. De Meyer, Annelies & Cattrysse, Dirk & Rasinmäki, Jussi & Van Orshoven, Jos, 2014. "Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 657-670.
    6. 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.
    7. Espinoza Pérez, Andrea Teresa & Camargo, Mauricio & Narváez Rincón, Paulo César & Alfaro Marchant, Miguel, 2017. "Key challenges and requirements for sustainable and industrialized biorefinery supply chain design and management: A bibliographic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 350-359.
    8. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    9. Babazadeh, Reza & Razmi, Jafar & Pishvaee, Mir Saman & Rabbani, Masoud, 2017. "A sustainable second-generation biodiesel supply chain network design problem under risk," Omega, Elsevier, vol. 66(PB), pages 258-277.
    10. Jensen, Ida Græsted & Münster, Marie & Pisinger, David, 2017. "Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses," European Journal of Operational Research, Elsevier, vol. 262(2), pages 744-758.
    11. Babazadeh, Reza, 2017. "Optimal design and planning of biodiesel supply chain considering non-edible feedstock," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1089-1100.
    12. Xie, Fei & Huang, Yongxi, 2018. "A multistage stochastic programming model for a multi-period strategic expansion of biofuel supply chain under evolving uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 130-148.
    13. Shabani, Nazanin & Sowlati, Taraneh & Ouhimmou, Mustapha & Rönnqvist, Mikael, 2014. "Tactical supply chain planning for a forest biomass power plant under supply uncertainty," Energy, Elsevier, vol. 78(C), pages 346-355.
    14. Malladi, Krishna Teja & Sowlati, Taraneh, 2018. "Biomass logistics: A review of important features, optimization modeling and the new trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 587-599.
    15. Huang, Yongxi & Chen, Yihsu, 2014. "Analysis of an imperfectly competitive cellulosic biofuel supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 1-14.
    16. Lee, Seonghee & Lee, Hakyeon, 2015. "Measuring and comparing the R&D performance of government research institutes: A bottom-up data envelopment analysis approach," Journal of Informetrics, Elsevier, vol. 9(4), pages 942-953.
    17. Ahn, Yu-Chan & Lee, In-Beum & Lee, Kun-Hong & Han, Jee-Hoon, 2015. "Strategic planning design of microalgae biomass-to-biodiesel supply chain network: Multi-period deterministic model," Applied Energy, Elsevier, vol. 154(C), pages 528-542.
    18. Fattahi, Mohammad & Govindan, Kannan, 2018. "A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: A real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 534-567.
    19. Osmani, Atif & Zhang, Jun, 2013. "Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties," Energy, Elsevier, vol. 59(C), pages 157-172.
    20. Ng, Rex T.L. & Kurniawan, Daniel & Wang, Hua & Mariska, Brian & Wu, Wenzhao & Maravelias, Christos T., 2018. "Integrated framework for designing spatially explicit biofuel supply chains," Applied Energy, Elsevier, vol. 216(C), pages 116-131.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:179:y:2019:i:c:p:1004-1016. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.