Discrete Diversity, Dispersion, and Coverage Subset Selection
R package Coreset version 1.0.0
Solves discrete location objectives on a distance matrix or
Euclidean coordinate set. The Max-Min Diversity (MMDP / p-dispersion)
objective, which maximizes the minimum pairwise distance within a selection
of k items, is solved by farthest-first selection (Gonzalez 1985)
<doi:10.1016/0304-3975(85)90224-5>; the DropAdd tabu-search heuristic
(Porumbel, Hao & Glover 2011) <doi:10.1007/s10479-011-0898-z>, GRASP with
path-relinking (Resende, Marti, Gallego & Duarte 2010)
<doi:10.1016/j.cor.2008.05.011>, and an exact node-packing integer program
(Sayyady & Fathi 2016) <doi:10.1016/j.ejor.2016.02.026>.
The Max-Mean Dispersion objective, which selects a subset of
unrestricted size maximising the sum of its pairwise distances divided by the
number of selected elements, is solved by reinforcement-learning-guided tabu
search (Nijimbere et al. 2020) <doi:10.3934/jimo.2020115>.
The discrete k-centre (min-max covering / facility location) objective,
which chooses k centres to minimise the largest distance from any point to
its nearest centre, is solved via the CDSh heuristic (Garcia-Diaz et al.
2017 <doi:10.1007/s10732-017-9345-x>, 2019 <doi:10.1109/ACCESS.2019.2933875>),
and an exact minimum-cover integer program. The maximum-entropy (maxdet)
objective, which maximises the log-determinant of a similarity kernel built
from the distances (Shewry & Wynn 1987 <doi:10.1080/02664768700000020>; the
mode of a determinantal point process, Kulesza & Taskar 2012
<doi:10.1561/2200000044>), is solved by greedy pivoted-Cholesky selection and,
for small instances, exact enumeration.
Software
Depends: R (>= 4.1)
Imports: cli (>= 3.0.0), Rcpp, Rdpack (>= 0.7), stats
LinkingTo: Rcpp
Suggests: highs, knitr, Matrix, quarto, rprojroot, spelling, testthat
(>= 3.0.0)
Martin R. Smith <martin.smith@durham.ac.uk>
Comprehensive R Archive Network (CRAN)
Martin R. Smith [aut, cre, cph] (ORCID:
<https://orcid.org/0000-0001-5660-1727>)
GPL (>= 3)
2026-09-17
application/tgz
https://CRAN.R-project.org/package=Coreset
doi:10.32614/CRAN.package.Coreset
en-GB