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Robust bi-objective cost-effective, multi-period, location-allocation organ transplant supply chain

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  • Seyed Mahdi Aghazadeh
  • Mohammad Mohammadi
  • Bahman Naderi

Abstract

This paper proposes a new multi-objective model for organ transplant supply chain under uncertainty conditions. Previous models have focused on time, location and allocations separately, and have not considered some important aspects in locating healthcare units. Because of the vital role of these parameters in decision-making about locating organ transplant supply chain, this new model compensates for and covers this shortcoming. These significant parameters include: 1) expected number of organs donors; 2) coverage rate of other zones for the selected locations based on cold ischemia time for each organ (cold ischemia time is the maximum time each organ can bear outside the body); 3) safety index based on earthquakes and other natural or unnatural events. The model consists of three objective functions: the first objective function reduces the costs of the active working centres. Transportations and allocations of units and organs, and the second objective function consider the mentioned parameters too. These objective functions are likely to face conflicts based on the input data. Finally, some statistics-based experiments have been conducted on the problem under study, and it has been solved using GAMS optimisation software (ver. 23.5).

Suggested Citation

  • Seyed Mahdi Aghazadeh & Mohammad Mohammadi & Bahman Naderi, 2018. "Robust bi-objective cost-effective, multi-period, location-allocation organ transplant supply chain," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 29(1), pages 17-36.
  • Handle: RePEc:ids:ijlsma:v:29:y:2018:i:1:p:17-36
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    Cited by:

    1. Alireza Goli & Ali Ala & Seyedali Mirjalili, 2023. "A robust possibilistic programming framework for designing an organ transplant supply chain under uncertainty," Annals of Operations Research, Springer, vol. 328(1), pages 493-530, September.

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