Other important and convenient agglomeration functions over time are weighted
p-norms,
i. e,\
(
) or
where 
is a weighting function with
almost everywhere. This can easily be generalized to
semi-norms in which 
may hold on a subset of [0, T] with
nonzero measure, but else. Weighting functions with this
property can also be introduced in (5.1). When interpreting e
as a sampling function, this means that some points (in time) are left
unsampled. The corresponding agglomeration functions include
i. e. only the effect at the end of the time interval considered
is accounted for.
Since there are too many different time agglomeration functions which are reasonable in different circumstances, no attempt has been made to provide the user of the software package with a number of templates. If agglomerations different from the one presently implemented are preferred, the source code of the optimization module has to be changed accordingly.