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Best points w.r.t. non dominated sorting with hypervolume contribution.

Source: R/nds_selection.R
nds_selection.Rd

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.

Usage

nds_selection(points, n_select, ref_point = NULL, minimize = TRUE)

Arguments

points

(matrix())
Numeric matrix with each column corresponding to a point

n_select

(integer(1L))
Amount of points to select.

ref_point

(numeric())
Reference point for hypervolume.

minimize

('logical()')
Should the ranking be based on minimization? Can be specified for each dimension or for all. Default is TRUE for each dimension.

Value

Vector of indices of selected points