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Optimizing the supply chain design for organ transplants

Author

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  • Belien, Jeroen

    (Hogeschool-Universiteit Brussel (HUB), Belgium)

  • De Boeck, Liesje

    (Hogeschool-Universiteit Brussel (HUB), Belgium)

  • Colpaert, Jan

    (Hogeschool-Universiteit Brussel (HUB), Belgium)

  • Devesse, Stijn
  • Van den Bossche, Filip

    (Hogeschool-Universiteit Brussel (HUB), Belgium)

Abstract

Organ transplants have always suffered from long waiting lists. This has led to time playing a crucial role in the organ transplant process. Therefore, from the moment a potential donor is notified, it is important to get the organ as quickly as possible to its recipient. The ultimate goal of this paper is to develop a general model in order to minimize this transport time. This is accomplished by jointly determining which transplant center(s) for which organ(s) to establish in a particular country (given the location of potential transplant centers), and the location of shipping agents for transportation of these organs. The problem is modeled as a mixed integer programming (MIP) problem. We then apply this model to organ transplants in Belgium. Extensive numerical experiments show that considering only the components influencing the cold ischemia time in the objective function, as well as a budget constraint or non binding time covering constraint, leads to the centralization of transplant centers. The MIP model performs well in terms of computation times except for the case involving a huge number of potential shipping agents.

Suggested Citation

  • Belien, Jeroen & De Boeck, Liesje & Colpaert, Jan & Devesse, Stijn & Van den Bossche, Filip, 2011. "Optimizing the supply chain design for organ transplants," Working Papers 2011/02, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    • Handle: RePEc:hub:wpecon:201102
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    References listed on IDEAS

    as
    1. Oguzhan Alagoz & Andrew J. Schaefer & Mark S. Roberts, 2009. "Optimizing Organ Allocation and Acceptance," Springer Optimization and Its Applications, in: H. Edwin Romeijn & Panos M. Pardalos (ed.), Handbook of Optimization in Medicine, chapter 1, pages 1-24, Springer.
    2. ReVelle, C.S. & Eiselt, H.A. & Daskin, M.S., 2008. "A bibliography for some fundamental problem categories in discrete location science," European Journal of Operational Research, Elsevier, vol. 184(3), pages 817-848, February.
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    Cited by:

    1. Caruso, Valeria & Daniele, Patrizia, 2018. "A network model for minimizing the total organ transplant costs," European Journal of Operational Research, Elsevier, vol. 266(2), pages 652-662.

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