  The lack of reliable atomic data can be a severe limitation in astrophysical
modelling, in particular of events such as kilonovae that require information
on all neutron-capture elements across a wide range of ionization stages.
Notably, the presence of non-orthonormalities between electron orbitals
representing configurations that are close in energy can introduce significant
inaccuracies in computed energies and transition probabilities. Here, we
propose an explicit targeted optimization method that can effectively
circumvent this concern while retaining an orthonormal orbital basis set. We
illustrate this method within the framework of small-scale atomic structure
models of Au I, using the GRASP2018 multiconfigurational Dirac-Hartree-Fock
atomic structure code. By comparing to conventional optimization schemes we
show how a targeted optimization approach improves the energy level positioning
and ordering. Targeted optimization also leads to better agreement with
experimental data for the strongest E1 transitions. This illustrates how
small-scale models can be significantly improved with minor computational costs
if orbital non-orthonormalities are considered carefully. These results should
prove useful to multi-element atomic structure calculations in, for example,
astrophysical opacity applications involving neutron-capture elements.
