In this paper a two-stage algorithm for finding non-
dominated subsets of partially ordered sets
is established. A connection is then made with dimension reduction in time-dependent
dynamic programming via the notion of a bounding label, a function that bounds
the state-transition cost functions. In this context, the computational burden is partitioned
between a time-independent dynamic programming step carried out on the bounding label and
a direct evaluation carried out on a subset of “real" valued decisions. A computational
application to time-dependent fuzzy dynamic programming is presented.