Conference item
Randomized assignments for barter exchanges: Fairness vs efficiency
- Abstract:
- We study fairness and efficiency properties of randomized algorithms for barter exchanges with direct applications to kidney exchange problems. It is well documented that randomization can serve as a tool to ensure fairness among participants. However, in many applications, practical constraints often restrict the maximum allowed cyclelength of the exchange and for randomized algorithms, this imposes constraints of the cycle-length of every realized exchange in their decomposition. We prove that standard fairness properties such as envy-freeness or symmetry are incompatible with even the weakest notion of economic efficiency in this setting. On the plus side, we adapt some well-known matching mechanisms to incorporate the restricted cycle constraint and evaluate their performance experimentally on instances of the kidney exchange problem, showing tradeoffs between fairness and efficiency.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 370.7KB, Terms of use)
-
- Publisher copy:
- 10.1007/978-3-319-23114-3_32
Authors
- Publisher:
- Springer International Publishing Switzerland
- Host title:
- ADT 2015: Algorithmic Decision Theory
- Journal:
- ADT 2015: Algorithmic Decision Theory More from this journal
- Pages:
- 537-552
- Series:
- Lecture Notes in Computer Science
- Publication date:
- 2015-08-28
- DOI:
- ISSN:
-
0302-9743, 1611-3349
- ISBN:
- 9783319231136
- Keywords:
- Pubs id:
-
pubs:578438
- UUID:
-
uuid:6ee83ebf-4b33-47cd-9ee5-47fd492d8682
- Local pid:
-
pubs:578438
- Deposit date:
-
2016-10-10
- ARK identifier:
Terms of use
- Copyright holder:
- Springer International Publishing Switzerland
- Copyright date:
- 2015
- Notes:
-
This is an
accepted manuscript of a journal article published by Springer in ADT 2015: Algorithmic Decision Theory on 2015-08-28, available online: http://dx.doi.org/10.1007/978-3-319-23114-3_32
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