A robust possibilistic programming framework for designing an organ transplant supply chain under uncertainty

Organ transplantation is a crucial task in the healthcare supply chain, which organizes the supply and demand for various vital organs. In this regard, dealing with uncertainty is one of the main challengings in designing an organ transplant supply chain. To address this gap, in the present research...

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Vydáno v:Annals of operations research Ročník 328; číslo 1; s. 493 - 530
Hlavní autoři: Goli, Alireza, Ala, Ali, Mirjalili, Seyedali
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2023
Springer Nature B.V
Témata:
Business and Management
Combinatorics
Mathematical analysis
Mathematical models
Operations research
Operations Research/Decision Theory
Optimization
Original Research
Robustness (mathematics)
Supply chains
Theory of Computation
Transplantation
Transplants
Transplants & implants
Uncertainty
Robust possibilistic programming
Healthcare operations
Organ transplantation
Simulation-based optimization
Fuzzy uncertainty
ISSN:0254-5330, 1572-9338
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Shrnutí:Organ transplantation is a crucial task in the healthcare supply chain, which organizes the supply and demand for various vital organs. In this regard, dealing with uncertainty is one of the main challengings in designing an organ transplant supply chain. To address this gap, in the present research, a mathematical formulation and solution method is proposed to optimize the organ transplants supply chain under shipment time uncertainty. A possibilistic programming model and simulation-based solution method are developed for organ transplant center location, allocation, and distribution. The proposed mathematical model optimizes the overall cost by considering the fuzzy uncertainty of organ demands and transportation time. Moreover, a novel simulation-based optimization is applied using the credibility theory to deal with the uncertainty in the optimization of this mathematical model. In addition, the proposed model and solution method are evaluated by implementing different test problems. The numerical results demonstrate that the optimal credibility level is between 0.2 and 0.6 in all tested cases. Moreover, the patient’s satisfaction rate is higher than the viability rate in the designed organ supply chain.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-022-04829-7