Select best subset of points by non dominated sorting with hypervolume contribution for tie breaking. Works on an arbitrary dimension of size two or higher.
nds_selection(points, n_select, ref_point = NULL, minimize = TRUE)
Vector of indices of selected points
(matrix()
)
Numeric matrix with each column corresponding to a point
(integer(1L)
)
Amount of points to select.
(numeric()
)
Reference point for hypervolume.
('logical()')
Should the ranking be based on minimization?
Can be specified for each dimension or for all.
Default is TRUE
for each dimension.