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A robust optimisation model for sustainable blood supply chain network design under uncertainty

Author

Listed:
  • Zahra Mohammadian-Behbahani
  • Armin Jabbarzadeh
  • Mir Saman Pishvaee

Abstract

Blood is a perishable, scarce and lifesaving product. While the demand for blood products has been increased over the past few decades, there has been no specified artificial alternative for this critical product yet. In this context, it is of paramount importance to design efficient, agile and effective blood supply chain networks. This paper presents a multi-objective stochastic programming model for blood supply chain network design by considering the following objectives: minimising total cost, minimising delivery time and maximising two important social measures including the indicator of consumer's health and the rate of regular blood donors. A robust optimisation approach is employed to incorporate different sources of uncertainties in demand and supply parameters. To investigate the performance and utility of the proposed formulation, the model is implemented using real data of blood transfusion network of Tehran.

Suggested Citation

  • Zahra Mohammadian-Behbahani & Armin Jabbarzadeh & Mir Saman Pishvaee, 2019. "A robust optimisation model for sustainable blood supply chain network design under uncertainty," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 31(4), pages 475-494.
  • Handle: RePEc:ids:ijisen:v:31:y:2019:i:4:p:475-494
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    Cited by:

    1. Ali Sibevei & Adel Azar & Mostafa Zandieh & Seyed Mohammad Khalili & Maziar Yazdani, 2022. "Developing a Risk Reduction Support System for Health System in Iran: A Case Study in Blood Supply Chain Management," IJERPH, MDPI, vol. 19(4), pages 1-19, February.
    2. Soheyl Khalilpourazari & Shima Soltanzadeh & Gerhard-Wilhelm Weber & Sankar Kumar Roy, 2020. "Designing an efficient blood supply chain network in crisis: neural learning, optimization and case study," Annals of Operations Research, Springer, vol. 289(1), pages 123-152, June.

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