Kidney Exchange: An Operations Perspective

Ashlagi, Itai; Roth, Alvin E.

doi:10.1287/mnsc.2020.3954

Cited by 26 publications

(7 citation statements)

References 144 publications

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“…Kidney exchange is one of the major research topics in matching market design (Abraham, Blum, and Sandholm 2007;Ashlagi and Roth 2020;Hatfield 2005;Biró, Manlove, and Rizzi 2009;Dickerson, Procaccia, and Sandholm 2014;Li et al 2019;Sönmez and Ünver 2011). In many of the papers, the algorithms only allow exchange cycles of limited size due to logistical and other constraints.…”

Section: Related Workmentioning

confidence: 99%

Optimal Kidney Exchange with Immunosuppressants

Aziz¹,

Cseh²,

Dickerson³

et al. 2021

Preprint

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Algorithms for exchange of kidneys is one of the key successful applications in market design, artificial intelligence, and operations research. Potent immunosuppressant drugs suppress the body's ability to reject a transplanted organ up to the point that a transplant across blood-or tissue-type incompatibility becomes possible. In contrast to the standard kidney exchange problem, we consider a setting that also involves the decision about which recipients receive from the limited supply of immunosuppressants that make them compatible with originally incompatible kidneys. We firstly present a general computational framework to model this problem. Our main contribution is a range of efficient algorithms that provide flexibility in terms of meeting meaningful objectives. Motivated by the current reality of kidney exchanges using sophisticated mathematical-programming-based clearing algorithms, we then present a general but scalable approach to optimal clearing with immunosuppression; we validate our approach on realistic data from a large fielded exchange.

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Section: Related Workmentioning

confidence: 99%

Optimal Kidney Exchange with Immunosuppressants

Aziz¹,

Cseh²,

Dickerson³

et al. 2021

Preprint

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“…Finally, an important example for an application where optimisation is used for the allocation are the kidney exchange programmes (KEPs), where kidney patients with incompatible donors may exchange their willing donor among themselves. Seminal work on IP models for KEP's is presented in [1] and [27], a recent survey is [7], and the European optimisation practices are summarised in [13]. It is interesting to note that online matching is used in the US, partly because of the competition in between multiple national programmes [2].…”

Section: Related Literaturementioning

confidence: 99%

“…x e ≤ q(a i , s k ) for every e ∈ E, (a i , s k ) ∈ e (7) When computing the volume of a solution, for groups we assume that the actual mentoring hours for a student (x t e ) is upper bounded by her original request in this subject, and by the number of mentoring hours of the group. This can be formalised with the following constraints…”

Section: Optimisation With Milp Techniquementioning

confidence: 99%

Online voluntary mentoring: Optimising the assignment of students and mentors

Bíró¹,

Gyetvai²

2021

Preprint

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After the closure of the schools in Hungary from March 2020 due to the pandemic, many students were left at home with no or not enough parental help for studying, and in the meantime some people had more free time and willingness to help others in need during the lockdown. In this paper we describe the optimisation aspects of a joint NGO project for allocating voluntary mentors to students using a web-based coordination mechanism. The goal of the project has been to form optimal pairs and study groups by taking into the preferences and the constraints of the participants. In this paper we present the optimisation concept, and the integer programming techniques used for solving the allocation problems. Furthermore, we conducted computation simulations on real and generated data for evaluate the performance of this dynamic matching scheme under different parameter settings.

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“…The case of bounded length cycles and unbounded length (aka never ending) chains was studied from an optimization aspect in [6], and was successfully implemented in a national US KEP, Alliance for Paired Donation (APD), as described in [5]. For recent surveys on the optimization aspects of KEPs, we refer to [23] and [8]; a review on KEP simulations can be found in [34].…”

Section: Related Literaturementioning

confidence: 99%

“…Accordingly, for finding a strongly stable exchange in the case of strict preferences constraints (8) in model ( 1)-( 9) must be replaced by:…”

Section: Edge Formulationmentioning

confidence: 99%

Novel Integer Programming models for the stable kidney exchange problem

Klimentova¹,

Bíró²,

Viana³

et al. 2020

Preprint

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Kidney exchange programs (KEP's) represent an additional possibility of transplant for patients suffering from end stage kidney disease. If a patient has a willing living donor with whom the patient is not compatible, the pair patient-donor can join a pool of incompatible pairs and, if compatibility between patient and donor in two our more pairs exists, organs can be exchanged between them. The problem can be modeled as an integer program that, in general, aims * This work is financed by the ERDF -European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization -COMPETE 2020 Programme, and by National Funds through the Portuguese funding agency, FCT -Fundação para a Ciência e a Tecnologia, within project "mKEP -Models and optimization algorithms for multicountry kidney exchange programs" (POCI-01-0145-FEDER-016677), by COST Action CA15210 ENCKEP, supported by COST (European Cooperation in Science and Technology) -http://www.cost.eu/. Biró is supported by the Hungarian Academy of Sciences under its Momentum Programme (LP2016-3), and by the Hungarian Scientific Research Fund -OTKA (no. K129086).

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Kidney Exchange: An Operations Perspective

Cited by 26 publications

References 144 publications

Optimal Kidney Exchange with Immunosuppressants

Optimal Kidney Exchange with Immunosuppressants

Online voluntary mentoring: Optimising the assignment of students and mentors

Novel Integer Programming models for the stable kidney exchange problem

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