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Mixed robust possibilistic flexible chance constraint optimization model for emergency blood supply chain network design

Author

Listed:
  • Mohamadreza Fazli-Khalaf

    (Kharazmi University)

  • Soheyl Khalilpourazari

    (Kharazmi University)

  • Mohammad Mohammadi

    (Kharazmi University)

Abstract

This research proposes a new tri-objective mathematical model for designing blood supply chain network in emergency situations. The mathematical model aims to minimize total supply chain costs and transportation time between facilities while maximizing total testing reliability of the donated blood in the laboratories. The model considers five echelons including blood donor groups, blood collection facilities, laboratories, blood centers and hospitals. Different transportation means with variant speed and capacity are considered in the model to carry the blood between facilities. Since, most of the main parameters of the mathematical model are tainted with uncertainty in real-world applications, two robust possibilistic flexible chance constraint programming (RPFCCP) and possibilistic flexible chance constraint programming models are developed to provide risk-averse and robust solutions to the decision makers. In addition, the application of the proposed multi-objective mathematical model is investigated in a real-world case study using real data on Iran’s capital, Tehran, which is considered to be a potential place for a destructive earthquake. Using different realizations, the applicability and efficiency of the models are investigated in the case study. The results indicated that the RPFCCP model is able to handle uncertainty in the parameters of the objective function and constraints more efficiently and is able to provide robust and risk-averse solutions for the problem which are resistant to different scenarios.

Suggested Citation

  • Mohamadreza Fazli-Khalaf & Soheyl Khalilpourazari & Mohammad Mohammadi, 2019. "Mixed robust possibilistic flexible chance constraint optimization model for emergency blood supply chain network design," Annals of Operations Research, Springer, vol. 283(1), pages 1079-1109, December.
  • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-017-2729-3
    DOI: 10.1007/s10479-017-2729-3
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    References listed on IDEAS

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    8. Tirkolaee, Erfan Babaee & Golpîra, Hêriş & Javanmardan, Ahvan & Maihami, Reza, 2023. "A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
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    10. Sheikholeslami, Mahnaz & Zarrinpoor, Naeme, 2023. "Designing an integrated humanitarian logistics network for the preparedness and response phases under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
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    13. Lin Chen & Ting Dong & Jin Peng & Dan Ralescu, 2023. "Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review," Mathematics, MDPI, vol. 11(11), pages 1-45, May.
    14. Kamyabniya, Afshin & Noormohammadzadeh, Zohre & Sauré, Antoine & Patrick, Jonathan, 2021. "A robust integrated logistics model for age-based multi-group platelets in disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
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    18. Esmaeili, Somayeh & Bashiri, Mahdi & Amiri, Amirhossein, 2023. "An exact criterion space search algorithm for a bi-objective blood collection problem," European Journal of Operational Research, Elsevier, vol. 311(1), pages 210-232.

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