IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i7p1491-d158026.html
   My bibliography  Save this article

Accounting for Fairness in a Two-Stage Stochastic Programming Model for Kidney Exchange Programs

Author

Listed:
  • Hyunwoo Lee

    (School of Industrial Management Engineering, Korea University, Seoul 02841, Korea)

  • Seokhyun Chung

    (School of Industrial Management Engineering, Korea University, Seoul 02841, Korea)

  • Taesu Cheong

    (School of Industrial Management Engineering, Korea University, Seoul 02841, Korea)

  • Sang Hwa Song

    (Graduate School of Logistics, Incheon National University, Incheon 22012, Korea)

Abstract

Kidney exchange programs, which allow a potential living donor whose kidney is incompatible with his or her intended recipient to donate a kidney to another patient in return for a kidney that is compatible for their intended recipient, usually aims to maximize the number of possible kidney exchanges or the total utility of the program. However, the fairness of these exchanges is an issue that has often been ignored. In this paper, as a way to overcome the problems arising in previous studies, we take fairness to be the degree to which individual patient-donor pairs feel satisfied, rather than the extent to which the exchange increases social benefits. A kidney exchange has to occur on the basis of the value of the kidneys themselves because the process is similar to bartering. If the matched kidneys are not of the level expected by the patient-donor pairs involved, the match may break and the kidney exchange transplantation may fail. This study attempts to classify possible scenarios for such failures and incorporate these into a stochastic programming framework. We apply a two-stage stochastic programming method using total utility in the first stage and the sum of the penalties for failure in the second stage when an exceptional event occurs. Computational results are provided to demonstrate the improvement of the proposed model compared to that of previous deterministic models.

Suggested Citation

  • Hyunwoo Lee & Seokhyun Chung & Taesu Cheong & Sang Hwa Song, 2018. "Accounting for Fairness in a Two-Stage Stochastic Programming Model for Kidney Exchange Programs," IJERPH, MDPI, vol. 15(7), pages 1-16, July.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1491-:d:158026
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/7/1491/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/7/1491/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Constantino, Miguel & Klimentova, Xenia & Viana, Ana & Rais, Abdur, 2013. "New insights on integer-programming models for the kidney exchange problem," European Journal of Operational Research, Elsevier, vol. 231(1), pages 57-68.
    2. Xuanming Su & Stefanos A. Zenios, 2005. "Patient Choice in Kidney Allocation: A Sequential Stochastic Assignment Model," Operations Research, INFORMS, vol. 53(3), pages 443-455, June.
    3. Dimitris Bertsimas & Vivek F. Farias & Nikolaos Trichakis, 2011. "The Price of Fairness," Operations Research, INFORMS, vol. 59(1), pages 17-31, February.
    4. Alireza Sabouri & Woonghee Tim Huh & Steven M. Shechter, 2017. "Screening Strategies for Patients on the Kidney Transplant Waiting List," Operations Research, INFORMS, vol. 65(5), pages 1131-1146, October.
    5. Tayfun Sönmez & Alvin E. Roth & M. Utku Ünver, 2007. "Efficient Kidney Exchange: Coincidence of Wants in Markets with Compatibility-Based Preferences," American Economic Review, American Economic Association, vol. 97(3), pages 828-851, June.
    6. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    7. Qipeng P. Zheng & Siqian Shen & Yuhui Shi, 2015. "Loss-constrained minimum cost flow under arc failure uncertainty with applications in risk-aware kidney exchange," IISE Transactions, Taylor & Francis Journals, vol. 47(9), pages 961-977, September.
    8. Dimitris Bertsimas & Vivek F. Farias & Nikolaos Trichakis, 2013. "Fairness, Efficiency, and Flexibility in Organ Allocation for Kidney Transplantation," Operations Research, INFORMS, vol. 61(1), pages 73-87, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zahra Gharibi & Michael Hahsler, 2021. "A Simulation-Based Optimization Model to Study the Impact of Multiple-Region Listing and Information Sharing on Kidney Transplant Outcomes," IJERPH, MDPI, vol. 18(3), pages 1-20, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tom Demeulemeester & Dries Goossens & Ben Hermans & Roel Leus, 2023. "Fair integer programming under dichotomous and cardinal preferences," Papers 2306.13383, arXiv.org, revised Apr 2024.
    2. Sepehr Nemati & Zeynep G. Icten & Lisa M. Maillart & Andrew J. Schaefer, 2020. "Mitigating Information Asymmetry in Liver Allocation," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 234-248, April.
    3. Li, Mengling & Riyanto, Yohanes E. & Xu, Menghan, 2022. "Remedying adverse selection in donor-priority rule using freeze period: Theory and experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 384-407.
    4. Carvalho, Margarida & Lodi, Andrea, 2023. "A theoretical and computational equilibria analysis of a multi-player kidney exchange program," European Journal of Operational Research, Elsevier, vol. 305(1), pages 373-385.
    5. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    6. Li, Mengling & Riyanto, Yohanes E. & Xu, Menghan, 2023. "Prioritized organ allocation rules under compatibility constraints," Games and Economic Behavior, Elsevier, vol. 141(C), pages 403-427.
    7. Gur, Yonatan & Iancu, Dan & Warnes, Xavier, 2020. "Value Loss in Allocation Systems with Provider Guarantees," Research Papers 3813, Stanford University, Graduate School of Business.
    8. Baris Ata & Yichuan Ding & Stefanos Zenios, 2021. "An Achievable-Region-Based Approach for Kidney Allocation Policy Design with Endogenous Patient Choice," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 36-54, 1-2.
    9. Glorie, K.M. & Wagelmans, A.P.M. & van de Klundert, J.J., 2012. "Iterative branch-and-price for hierarchical multi-criteria kidney exchange," Econometric Institute Research Papers EI 2012-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Sahar Ahmadvand & Mir Saman Pishvaee, 2018. "An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach," Health Care Management Science, Springer, vol. 21(4), pages 587-603, December.
    11. Turgay Ayer & Can Zhang & Anthony Bonifonte & Anne C. Spaulding & Jagpreet Chhatwal, 2019. "Prioritizing Hepatitis C Treatment in U.S. Prisons," Operations Research, INFORMS, vol. 67(3), pages 853-873, May.
    12. Klimentova, Xenia & Biró, Péter & Viana, Ana & Costa, Virginia & Pedroso, João Pedro, 2023. "Novel integer programming models for the stable kidney exchange problem," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1391-1407.
    13. John P. Dickerson & Ariel D. Procaccia & Tuomas Sandholm, 2019. "Failure-Aware Kidney Exchange," Management Science, INFORMS, vol. 65(4), pages 1768-1791, April.
    14. Zahra Gharibi & Michael Hahsler, 2021. "A Simulation-Based Optimization Model to Study the Impact of Multiple-Region Listing and Information Sharing on Kidney Transplant Outcomes," IJERPH, MDPI, vol. 18(3), pages 1-20, January.
    15. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Xie, Ying, 2022. "Service fairness and value of customer information for the stochastic container relocation problem under flexible service policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    16. Kratz, Jörgen, 2024. "Conflicting objectives in kidney exchange," Journal of Economic Theory, Elsevier, vol. 217(C).
    17. Sinem Savaşer & Ömer Burak Kınay & Bahar Yetis Kara & Pelin Cay, 2019. "Organ transplantation logistics: a case for Turkey," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 327-356, June.
    18. Hussein El Hajj & Douglas R. Bish & Ebru K. Bish, 2021. "Equity in genetic newborn screening," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 44-64, February.
    19. Can Zhang & Atalay Atasu & Turgay Ayer & L. Beril Toktay, 2020. "Truthful Mechanisms for Medical Surplus Product Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 735-753, July.
    20. Kargar, Bahareh & Pishvaee, Mir Saman & Jahani, Hamed & Sheu, Jiuh-Biing, 2020. "Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1491-:d:158026. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.