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

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Abstract

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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Authors and Affiliations

  1. Department of Industrial Engineering and Future Studies, Faculty of Engineering, University of Isfahan, Isfahan, 8174673441, Iran

    Alireza Goli

  2. Department of Industrial Engineering & Management, School of Mechanical Engineering, Shanghai Jiao Tong University, 200240, Shanghai, China

    Ali Ala

  3. Centre for Artificial Intelligence Research and Optimization, Torrens University Australia, Fortitude Valley, Brisbane, Fortitude Valley, QLD, 4006, Australia

    Seyedali Mirjalili

  4. Yonsei Frontier Lab, Yonsei University, Seoul, South Korea

    Seyedali Mirjalili

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  1. Alireza Goli
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  2. Ali Ala
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Correspondence to Alireza Goli.

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Goli, A., Ala, A. & Mirjalili, S. A robust possibilistic programming framework for designing an organ transplant supply chain under uncertainty. Ann Oper Res 328, 493–530 (2023). https://doi.org/10.1007/s10479-022-04829-7

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