k individuals are chosen randomly and the best one
is chosen. This process is repeated n.select
times.
Choice is primarily by dominated sorting
and secondarily by either dominated hypervolume
or crowding distance, depending on sorting
.
Ties are broken randomly by adding random noise of relative magnitude
.Machine$double.eps * 2^10
to points.
selTournamentMO(
fitness,
n.select,
sorting = "crowding",
ref.point,
k = 2,
return.unique = FALSE
)
[integer]
vector of selected individuals.
[matrix]
fitness matrix, one column per individual.
[integer(1)]
number of individuals to select.
[character(1)]
one of "domhv"
or "crowding"
(default).
[numeric]
reference point for hypervolume, must be given
if sorting
is "domhv"
.
[integer(1)]
number of individuals to select at once.
[logical(1)]
whether returned individual indices must be unique.
Other Selectors:
selSimpleUnique()