Improved instance generation for kidney exchange programmes
Delorme,Maxence García,Sergio Gondzio,Jacek Kalcsics,Jörg Manlove,David Pettersson,William Trimble,James
Delorme,Maxence
García,Sergio
Gondzio,Jacek
Kalcsics,Jörg
Manlove,David
Pettersson,William
Trimble,James
Abstract
Kidney exchange programmes increase the rate of living donor kidney transplants, and operations research techniques are vital to such programmes. These techniques, as well as changes to policy regarding kidney exchange programmes, are often tested using random instances created by a Saidman generator. We show that instances produced by such a generator differ from real-world instances across a number of important parameters, including the average number of recipients that are compatible with a certain donor. We exploit these differences to devise powerful upper and lower bounds and we demonstrate their effectiveness by optimally solving a benchmark set of Saidman instances in seconds; this set could not be solved in under thirty minutes with previous algorithms. We then present new techniques for generating random kidney exchange instances that are far more consistent with real-world instances from the UK kidney exchange programme. This new process for generating random instances provides a more accurate base for comparisons of algorithms and models, and gives policy-makers a better understanding of potential changes to policy leading to an improved decision-making process.
Description
Funding Information: The authors would like to thank the two anonymous reviewers for their valuable comments that have helped to improve the presentation of this paper, and NHS Blood and Transplant for sharing their data and experience with us. This research was supported by the Engineering and Physical Science Research Council, United Kingdom through grant numbers EP/P028306/1 (Manlove and Pettersson), EP/P029825/1 (Delorme, García, Gondzio, and Kalcsics), and EP/R513222/1 (Trimble).
Date
2022-05
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Research Projects
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Keywords
Kidney exchange, Matheuristic, Saidman generator
Citation
Delorme, M, García, S, Gondzio, J, Kalcsics, J, Manlove, D, Pettersson, W & Trimble, J 2022, 'Improved instance generation for kidney exchange programmes', Computers & Operations Research, vol. 141, 105707. https://doi.org/10.1016/j.cor.2022.105707