Abstract:We study the computational problem of identifying optimal sets of kidney exchanges in the UK. We show how to expand an integer programming-based formulation due to Roth et al. [2007] in order to model the criteria that constitute the UK definition of optimality. The software arising from this work has been used by the National Health Service Blood and Transplant to find optimal sets of kidney exchanges for their National Living Donor Kidney Sharing Schemes since July 2008. We report on the characteristics of t… Show more
“…Kidney-exchange schemes exist in several countries to increase the number of transplants from living donors to patients with end-stage renal disease [24,35,47]. A patient enters the scheme along with a friend or family member who is willing to donate to that patient but unable to do so due to blood or tissue incompatibility.…”
Section: Kidney Exchangementioning
confidence: 99%
“…The weighting scheme and exchange size cap we used are based on the system used in the UK's National Living Donor Kidney Sharing Scheme (NLDKSS) [35]. The NLDKSS has a maximum exchange size of three, and has five objectives, ranked hierarchically.…”
Section: Kidney Exchangementioning
confidence: 99%
“…We use a simple transformation to convert the third objective from a minimisation to a maximisation. This method of combining scores in order to perform a single optimisation is not practical using IP solvers because, as Manlove and O'Malley [35] observe, the resulting weights would be too large for IP solvers. By contrast, all of our maximum-weight clique solvers can use 64-bit weights without loss of precision.…”
Abstract. Maximum weight clique and maximum weight independent set solvers are often benchmarked using maximum clique problem instances, with weights allocated to vertices by taking the vertex number mod 200 plus 1. For constraint programming approaches, this rule has clear implications, favouring weight-based rather than degree-based heuristics. We show that similar implications hold for dedicated algorithms, and that additionally, weight distributions affect whether certain inference rules are cost-effective. We look at other families of benchmark instances for the maximum weight clique problem, coming from winner determination problems, graph colouring, and error-correcting codes, and introduce two new families of instances, based upon kidney exchange and the Research Excellence Framework. In each case the weights carry much more interesting structure, and do not in any way resemble the 200 rule. We make these instances available in the hopes of improving the quality of future experiments.
“…Kidney-exchange schemes exist in several countries to increase the number of transplants from living donors to patients with end-stage renal disease [24,35,47]. A patient enters the scheme along with a friend or family member who is willing to donate to that patient but unable to do so due to blood or tissue incompatibility.…”
Section: Kidney Exchangementioning
confidence: 99%
“…The weighting scheme and exchange size cap we used are based on the system used in the UK's National Living Donor Kidney Sharing Scheme (NLDKSS) [35]. The NLDKSS has a maximum exchange size of three, and has five objectives, ranked hierarchically.…”
Section: Kidney Exchangementioning
confidence: 99%
“…We use a simple transformation to convert the third objective from a minimisation to a maximisation. This method of combining scores in order to perform a single optimisation is not practical using IP solvers because, as Manlove and O'Malley [35] observe, the resulting weights would be too large for IP solvers. By contrast, all of our maximum-weight clique solvers can use 64-bit weights without loss of precision.…”
Abstract. Maximum weight clique and maximum weight independent set solvers are often benchmarked using maximum clique problem instances, with weights allocated to vertices by taking the vertex number mod 200 plus 1. For constraint programming approaches, this rule has clear implications, favouring weight-based rather than degree-based heuristics. We show that similar implications hold for dedicated algorithms, and that additionally, weight distributions affect whether certain inference rules are cost-effective. We look at other families of benchmark instances for the maximum weight clique problem, coming from winner determination problems, graph colouring, and error-correcting codes, and introduce two new families of instances, based upon kidney exchange and the Research Excellence Framework. In each case the weights carry much more interesting structure, and do not in any way resemble the 200 rule. We make these instances available in the hopes of improving the quality of future experiments.
“…This program consists on contacting CKD patients that have a voluntary living kidney donor (a relative, spouse or a friend) with no histocompatibility and they are willing to participate in finding a couple in the same situation (no donor-recipient histocompatibility) and swap donors. The KEP has been implemented in countries such as South Korea (6), Switzerland (7), The United States (8)(9)(10), Turkey (11), Romania (12), Netherlands (13)(14)(15), United Kingdom (16)(17)(18), Portugal, Canada, New Zealand, and Australia (19).…”
Objective: This paper presents an analysis of two regulatory proposals in response to the growing demand for kidney transplants in Colombia. The results can be useful in evaluating these possible policy interventions once they have been implemented. Methods: The proposed model uses System Dynamics as a tool to understand the behavior of this complex social system if two intervention projects are executed. The first is a bill of law seeking to expand the legal presumption of organ donation. The second one is to implement a Kidney Exchange Program. The analysis is made in two parts. Firstly, a causal loop diagram is proposed. Secondly, the simulation of the system using a stock and flow diagram is analyzed. Results: Results show that the projects can balance the system and encourage donations. Conclusion: The implementation of a KEP is recommended since it achieves stability of the system earlier than the amendment to the law, with a reduction in the waiting list size.
“…Furthermore, Constantino et al [18] proposed two compact formulations-that is, an edge-assignment (EA) formulation and an extended edge (EE) formulation. Manlove and O'Malley [19] presented how the cycle formulation by Roth et al [17] can be extended to find optimal solutions for the KEP in the United Kingdom, which are compatible with U.K. National Living Donor Kidney Sharing Schemes (NLDKSS).…”
Kidney exchange allows a potential living donor whose kidney is incompatible with his intended recipient to donate a kidney to another patient so that the donor's intended recipient can receive a compatible kidney from another donor. These exchanges can include cycles of longer than two donor-patient pairs and chains produced by altruistic donors. Kidney exchange programs (KEPs) can be modeled as a maximum-weight cycle-packing problem in a directed graph. This paper develops a new integer programming model for KEPs by applying the reformulation-linearization technique (RLT) to enhance a lower bound obtained by its linear programming (LP) relaxation. Given the results obtained from the proposed model, the model is expected to be utilized in the integrated KEP IT (Information Technology) healthcare platform to obtain plans for optimized kidney exchanges.
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