Processing, Please wait...

  • Home
  • About Us
  • Search:
  • Advanced Search

Growing Science » International Journal of Industrial Engineering Computations » Enhancing kidney transplantation through multi-agent kidney exchange programs: A comprehensive review and optimization models

Journals

  • IJIEC (726)
  • MSL (2637)
  • DSL (649)
  • CCL (508)
  • USCM (1092)
  • ESM (404)
  • AC (562)
  • JPM (247)
  • IJDS (912)
  • JFS (91)
  • HE (26)
  • SCI (26)

IJIEC Volumes

    • Volume 1 (17)
      • Issue 1 (9)
      • Issue 2 (8)
    • Volume 2 (68)
      • Issue 1 (12)
      • Issue 2 (20)
      • Issue 3 (20)
      • Issue 4 (16)
    • Volume 3 (76)
      • Issue 1 (9)
      • Issue 2 (15)
      • Issue 3 (20)
      • Issue 4 (12)
      • Issue 5 (20)
    • Volume 4 (50)
      • Issue 1 (14)
      • Issue 2 (10)
      • Issue 3 (12)
      • Issue 4 (14)
    • Volume 5 (47)
      • Issue 1 (13)
      • Issue 2 (12)
      • Issue 3 (12)
      • Issue 4 (10)
    • Volume 6 (39)
      • Issue 1 (7)
      • Issue 2 (12)
      • Issue 3 (10)
      • Issue 4 (10)
    • Volume 7 (47)
      • Issue 1 (10)
      • Issue 2 (14)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 8 (30)
      • Issue 1 (9)
      • Issue 2 (7)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 9 (32)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (7)
      • Issue 4 (10)
    • Volume 10 (34)
      • Issue 1 (8)
      • Issue 2 (10)
      • Issue 3 (8)
      • Issue 4 (8)
    • Volume 11 (36)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (9)
      • Issue 4 (10)
    • Volume 12 (29)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 13 (41)
      • Issue 1 (10)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 14 (50)
      • Issue 1 (11)
      • Issue 2 (15)
      • Issue 3 (9)
      • Issue 4 (15)
    • Volume 15 (55)
      • Issue 1 (19)
      • Issue 2 (15)
      • Issue 3 (12)
      • Issue 4 (9)
    • Volume 16 (75)
      • Issue 1 (12)
      • Issue 2 (15)
      • Issue 3 (19)
      • Issue 4 (29)

Keywords

Supply chain management(163)
Jordan(161)
Vietnam(148)
Customer satisfaction(120)
Performance(113)
Supply chain(108)
Service quality(98)
Tehran Stock Exchange(94)
Competitive advantage(93)
SMEs(86)
optimization(84)
Financial performance(83)
Trust(81)
TOPSIS(80)
Job satisfaction(79)
Sustainability(79)
Factor analysis(78)
Social media(78)
Knowledge Management(77)
Genetic Algorithm(76)


» Show all keywords

Authors

Naser Azad(82)
Mohammad Reza Iravani(64)
Zeplin Jiwa Husada Tarigan(60)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(39)
Jumadil Saputra(36)
Dmaithan Almajali(36)
Muhammad Turki Alshurideh(35)
Barween Al Kurdi(32)
Ahmad Makui(32)
Basrowi Basrowi(31)
Hassan Ghodrati(31)
Mohammad Khodaei Valahzaghard(30)
Shankar Chakraborty(29)
Ni Nyoman Kerti Yasa(29)
Sulieman Ibraheem Shelash Al-Hawary(28)
Prasadja Ricardianto(28)
Sautma Ronni Basana(27)
Haitham M. Alzoubi(27)


» Show all authors

Countries

Iran(2177)
Indonesia(1278)
Jordan(784)
India(782)
Vietnam(500)
Saudi Arabia(440)
Malaysia(438)
United Arab Emirates(220)
China(182)
Thailand(151)
United States(110)
Turkey(103)
Ukraine(102)
Egypt(97)
Canada(92)
Pakistan(84)
Peru(83)
Morocco(79)
United Kingdom(79)
Nigeria(77)


» Show all countries

International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 16 Issue 2 pp. 483-498 , 2025

Enhancing kidney transplantation through multi-agent kidney exchange programs: A comprehensive review and optimization models Pages 483-498 Right click to download the paper Download PDF

Authors: Shayan Sharifi

DOI: 10.5267/j.ijiec.2024.12.002

Keywords: Kidney Transplantation, Kidney Exchange Programs (KEP), HLA, Multi-Agent Kidney Exchange (MKEP), Fairness

Abstract: This paper presents a comprehensive review of the last two decades of research on Kidney Exchange Programs (KEPs), systematically categorizing and classifying key contributions to provide readers with a structured understanding of advancements in the field. The review highlights the evolution of KEP methodologies and lays the foundation for our contribution. We propose three mathematical models aimed at improving both the quantity and quality of kidney transplants. Model 1 maximizes the number of transplants by focusing on compatibility based on blood type and PRA, without additional constraints. Model 2 introduces a minimum Human Leukocyte Antigen (HLA) compatibility threshold to enhance transplant quality, though this leads to fewer matches. Model 3 extends the problem to a Multi-Agent Kidney Exchange Program (MKEP), pooling incompatible donor-recipient pairs across multiple agents, resulting in a higher number of successful transplants while ensuring fairness across agents. Sensitivity analyses demonstrate trade-offs between transplant quantity and quality, with Model 3 striking the optimal balance by leveraging multi-agent collaboration to improve both the number and quality of transplants. These findings underscore the potential benefits of more integrated kidney exchange systems.

How to cite this paper
Sharifi, S. (2025). Enhancing kidney transplantation through multi-agent kidney exchange programs: A comprehensive review and optimization models.International Journal of Industrial Engineering Computations , 16(2), 483-498.

Refrences
Abraham, D. J., Blum, A., & Sandholm, T. (2007, June). Clearing algorithms for barter exchange markets: Enabling nationwide kidney exchanges. In Proceedings of the 8th ACM conference on Electronic commerce (pp. 295-304).Agarwal, N. A. (2019). Market failure in kidney exchange. American Economic Review, 4026-4070.
Agarwal, N., Ashlagi, I., Azevedo, E., Featherstone, C. R., & Karaduman, Ö. (2019). Market failure in kidney exchange. American Economic Review, 109(11), 4026-4070.Alvelos, F. K. (2015). A compact formulation for maximizing the expected number of transplants in kidney exchange programs. Journal of Physics: Conference Series.
Ahmadvand, S., & Pishvaee, M. S. (2018). An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach. Health care management science, 21, 587-603.
Alvelos, F. K. (2015). A compact formulation for maximizing the expected number of transplants in kidney exchange programs. Journal of Physics: Conference Series.
Alvelos, F., Klimentova, X., & Viana, A. (2019). Maximizing the expected number of transplants in kidney exchange programs with branch-and-price. Annals of Operations Research, 272(1), 429-444.
Anderson, R., Ashlagi, I., Gamarnik, D., & Roth, A. E. (2015). Finding long chains in kidney exchange using the traveling salesman problem. Proceedings of the National Academy of Sciences, 112(3), 663-668.
Ashlagi, I., & Roth, A. E. (2014). Free riding and participation in large scale, multi‐hospital kidney exchange. Theoretical Economics, 9(3), 817-863.
Bay, W. H., & HEBERT, L. A. (1987). The living donor in kidney transplantation. Annals of internal medicine, 106(5), 719-727.
Benedek, M., Biró, P., Kern, W., & Paulusma, D. (2021). Computing international kidney exchange schemes. In 16th International Symposium on Operational Research in Slovenia, SOR 2021 (pp. 61-61). Croatian Operational Research Society.
Caruso, V., & Daniele, P. (2018). A network model for minimizing the total organ transplant costs. European Journal of Operational Research, 266(2), 652-662.
Clark, B., & Unsworth, D. J. (2010). HLA and kidney transplantation. Journal of clinical pathology, 63(1), 21-25.
Constantino, M., Klimentova, X., Viana, A., & Rais, A. (2013). New insights on integer-programming models for the kidney exchange problem. European Journal of Operational Research, 231(1), 57-68.
Dharia, A. A., Huang, M., Nash, M. M., Dacouris, N., Zaltzman, J. S., & Prasad, G. R. (2022). Post-transplant outcomes in recipients of living donor kidneys and intended recipients of living donor kidneys. BMC nephrology, 23(1), 97.
Dickerson, J. P., Manlove, D. F., Plaut, B., Sandholm, T., & Trimble, J. (2016, July). Position-indexed formulations for kidney exchange. In Proceedings of the 2016 ACM Conference on Economics and Computation (pp. 25-42). Ghanbariamin, R. &. (2020). The effect of the National Kidney Registry on the kidney-exchange market. Journal of health economics.
Glorie, K., Carvalho, M., Constantino, M., Bouman, P., & Viana, A. (2015). Robust models for the kidney exchange problem. Working paper.
Glorie, K., Haase‐Kromwijk, B., van de Klundert, J., Wagelmans, A., & Weimar, W. (2014). Allocation and matching in kidney exchange programs. Transplant International, 27(4), 333-343.
Glorie, K., Wagelmans, A., & van de Klundert, J. (2012). Iterative branch-and-price for large multi-criteria kidney exchange. Econometric institute report, 11, 2012.
Health Resources and Service Administration (HRSA): https://www.organdonor.gov/learn/organ-donation-statistics
Horvat, L. D., Shariff, S. Z., Garg, A. X., & Donor Nephrectomy Outcomes Research (DONOR) Network. (2009). Global trends in the rates of living kidney donation. Kidney international, 75(10), 1088-1098.
Klimentova, X., Alvelos, F., & Viana, A. (2014). A new branch-and-price approach for the kidney exchange problem. In Computational Science and Its Applications–ICCSA 2014: 14th International Conference, Guimarães, Portugal, June 30–July 3, 2014, Proceedings, Part II 14 (pp. 237-252). Springer International Publishing.
Kutlu-Gündoğdu, F., Üney-Yüksektepe, F., Aktin, T., & Akin, B. (2018). A mathematical programming approach to paired kidney exchange: the case of Turkey.
Lee, H., Chung, S., Cheong, T., & Song, S. H. (2018). Accounting for fairness in a two-stage stochastic programming model for kidney exchange programs. International journal of environmental research and public health, 15(7), 1491.
Li, Y., Li, J., Fu, Q., Chen, L., Fei, J., Deng, S., ... & Wang, C. (2016, October). Kidney transplantation from brain-dead donors: Initial experience in China. In Transplantation Proceedings (Vol. 48, No. 8, pp. 2592-2595). Elsevier.
Li, Y., Song, P. X. K., Zhou, Y., Leichtman, A. B., Rees, M. A., & Kalbfleisch, J. D. (2014). Optimal decisions for organ exchanges in a kidney paired donation program. Statistics in biosciences, 6, 85-104.
Li, Z., Lieberman, K., Macke, W., Carrillo, S., Ho, C. J., Wellen, J., & Das, S. (2019, June). Incorporating compatible pairs in kidney exchange: A dynamic weighted matching model. In Proceedings of the 2019 ACM Conference on Economics and Computation (pp. 349-367).
Mincu, R. S., Biró, P., Gyetvai, M., Popa, A., & Verma, U. (2021). IP solutions for international kidney exchange programmes. Central European Journal of Operations Research, 29, 403-423.
Organ Procurement and Transplantation Network (OPT), 2023: https://optn.transplant.hrsa.gov/news/continued-increase-in-organ-donation-drives-new-records-in-2023-new-milestones-exceeded/
Pansart, L., Cambazard, H., Catusse, N., & Stauffer, G. (2018, June). Column generation for the kidney exchange problem. In 12 th International Conference on MOdeling, Optimization and SIMlation-MOSIM18.
Rapaport, F. T. (1986, June). The case for a living emotionally related international kidney donor exchange registry. In Transplantation proceedings (Vol. 18, No. 3) Suppl. 2, pp. 5-9).
Savaşer, S., Kınay, Ö. B., Kara, B. Y., & Cay, P. (2019). Organ transplantation logistics: a case for Turkey. OR spectrum, 41, 327-356.
Yuh, J., Chung, S., & Cheong, T. (2017). Reformulation-linearization technique approach for kidney exchange program IT healthcare platforms. Applied Sciences, 7(8), 847.
Zahiri, B., Tavakkoli-Moghaddam, R., & Pishvaee, M. S. (2014). A robust possibilistic programming approach to multi-period location–allocation of organ transplant centers under uncertainty. Computers & industrial engineering, 74, 139-148.
Zahiri, B., Tavakkoli-Moghaddam, R., Mohammadi, M., & Jula, P. (2014). Multi-objective design of an organ transplant network under uncertainty. Transportation research part E: logistics and transportation review, 72, 101-124.
Zheng, Q. P., Shen, S., & Shi, Y. (2015). Loss-constrained minimum cost flow under arc failure uncertainty with applications in risk-aware kidney exchange. Iie Transactions, 47(9), 961-977.
UNOS: https://unos.org/news/2022-organ-transplants-again-set-annual-records/
  • 17
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: International Journal of Industrial Engineering Computations | Year: 2025 | Volume: 16 | Issue: 2 | Views: 362 | Reviews: 0

Related Articles:
  • A fuzzy optimization approach to strategic organ transplantation network de ...
  • In vitro anti-BK polyomavirus activity of imidazo[1,2-c]pyrimidine and pyri ...
  • Modifications of total synthesis of mycophenolic acid
  • Solving a bi-objective mathematical programming model for bloodmobiles loca ...
  • Investigating the effects of liquidity and exchange rate on Tehran Stock Ex ...

Add Reviews

Name:*
E-Mail:
Review:
Bold Italic Underline Strike | Align left Center Align right | Insert smilies Insert link URLInsert protected URL Select color | Add Hidden Text Insert Quote Convert selected text from selection to Cyrillic (Russian) alphabet Insert spoiler
winkwinkedsmileam
belayfeelfellowlaughing
lollovenorecourse
requestsadtonguewassat
cryingwhatbullyangry
Security Code: *
Include security image CAPCHA.
Refresh Code

® 2010-2025 GrowingScience.Com