Multi-agent Kidney Exchange Program: dataset for simulation along time horizon

The dataset contains the instances files for the paper X. Klimentova, A. Viana, J. P. Pedroso, N. Santos. Fairness models for multi-agent kidney exchange programmes. To appear in Omega: The International Journal of Management Science (2020). The same dataset was also use in Monteiro, T., Klimentova, X., Pedroso, J.P.Pedroso, A. Viana. A comparison of matching algorithms for kidney exchange programs addressing waiting time. Cent Eur J Oper Res (2020). https://doi.org/10.1007/s10100-020-00680-y

Each instance mimics pools of kidney exchange progammes of several agents (e.g. countires) over time. Incompatible donor-recipient pairs appear and leave along the time horizon. Each of the pairs belongs to the pool of one of the agents. The virutal compatiblity among pairs is represented on a directed graph G = (V,A), called compatibility graph, where the set of vertices V corresponds to the set of incompatible pairs and non-directed donors. An arc from a vertex i to a vertex j indicates compatibility of donor in i with the patient in j. The positive real crossmatch testing is also incorporated by saving the arcs that would fail in case they are chosen is a cycle in one of the matching runs. The generator creates randomly graphs based on probabilities of blood type and of donor–patient tissue compatibility; the arrival of pairs and non-directed donors is generated based on a given arrival rates. An instance of the dataset represents a pools of 4 agents, that are simulated for the period of 6 years.

There are 100 instances compressed in 4 zip-archives, each containing 25 instances. Each of the instances is described by 3 files, where index s is the seed used for random function when generating the instance.

a) characterisations_s.csv -- csv file that contains information on each pair in the merged pool in the following columns

0 :  Pair ID

1 : Donor ID

2 : Donor blood type

3 : Donor age

4 : Patient ID

5 : Patient blood type

6 : Patient PRA

7 : Patient cross-match probability

8 : Patient age

9 : Pair arrival day

10 : Pair departure day

11 : Pair probability of failure

12 : Pair from pool (e.g. country to which the pair belongs to)

In case of non-directed donor the information about the patient is filled by -1;

b) acrs_s.csv - csv file containts the compatibility graph of the problem described above. In the first line the file contains values n – number of vertices in the graph and m – number of arcs in the graph. In the following m lines of the file, the existing arcs (i,j) are presented as follows: i j w_ij where i and j are IDs of pairs, w_ij is the weight of the arc, which is always equal to 1.0 for all the instances in this dataset.

c) fail_arcs_s.csv - is the list of arcs that would fail due to positive crossmatch test in case they appear in a chosen cycle or chain in any matching run. The format of the file is the same as that for arcs_s.csv. The first line represents the n - number of vertices in the graph, and m_fail the number of failed arcs listed in the following m_fail lines in the same way as in arcs_s.csv

Data and Resources

Additional Info

Field Value
Source The multi-agent generator is base on a single agent generator, proposed in N. Santos, P. Tubertini, A. Viana, and J.P. Pedroso. Kidney exchange simulation and optimization.Journal of the Operational Research Society, pages 1–12, 12 2017.
Author Xenia Klimentova, Ana Viana, João Pedro Pedroso, Nicolau Santos
Last Updated June 17, 2020, 14:53 (Europe/Lisbon)
Created June 16, 2020, 16:22 (Europe/Lisbon)
CiteAs KLIMENTOVA, X., VIANA, A., PEDROSO, J.P., SANTOS, N. Multi-agent Kidney Exchange Program: dataset for simulation along time horizon [dataset]. 16 June 2020. INESC TEC research data repository. DOI: https://doi.org/10.25747/kw8a-gn25
DOI https://doi.org/10.25747/kw8a-gn25
dc.Contributor The generator was developed based on the generator, proposed in N. Santos, P. Tubertini, A. Viana, and J.P. Pedroso. Kidney exchange simulation and optimization.Journal of the Operational Research Society, pages 1–12, 12 2017
dc.Coverage.Spatial CEGI, INESC TEC, Porto, Portugal
dc.Date 2017
dc.Format *.txt, *.csv, *.py, *.zip
dc.Format.Extent 177 MB
dc.Language EN
dc.Publisher INESC TEC
dc.Relation 1. X. Klimentova, A. Viana, J. P. Pedroso, N. Santos. Fairness models for multi-agent kidney exchange programmes. To appear in Omega: The International Journal of Management Science (2020). 2. Monteiro, T., Klimentova, X., Pedroso, J.P., Viana, A.. A comparison of matching algorithms for kidney exchange programs addressing waiting time. Cent Eur J Oper Res (2020). https://doi.org/10.1007/s10100-020-00680-y
dc.Type Compatibility graph and characteristics of the vertices for multi-agent Kidney Exchange Problem, evolving along time horizon of 6 years.
ddi.InstrumentType The generator used for generation of the instances is implemented in Python programming language