We investigate a generic, informal constrained optimization problem for which
there is uncertainty about a constraint parameter. To be able to deal with it
formally, we reformulate it as a decision problem under uncertainty, in which
the uncertainty is in general expressed using a set of probabilities. Our goal
is to end up with a constrained optimization problem without uncertainty and
this for different classes of sets of probabilities and different optimality
criteria. Some results will be presented, and the problem and our approach will
be illustrated using a pair of simple engineering problems.