  In this note we aim at putting more emphasis on the fact that trying to solve
non-convex optimization problems with coordinate-descent iterative linear
matrix inequality algorithms leads to suboptimal solutions, and put forward
other optimization methods better equipped to deal with such problems (having
theoretical convergence guarantees and/or being more efficient in practice).
This fact, already outlined at several places in the literature, still appears
to be disregarded by a sizable part of the systems and control community. Thus,
main elements on this issue and better optimization alternatives are presented
and illustrated by means of an example.
