  The Product Data Model (PDM) is an example of a data-centric approach to
modelling information-intensive business processes, which offers exibility and
facilitates process optimization. Because the approach is declarative in
nature, there may be multiple, alternative execution plans that can produce the
desired end product. To generate such plans, several heuristics have been
proposed in the literature. The contributions of this work are twofold: (i) we
propose new heuristics that capitalize on established techniques for optimizing
data-intensive work ows in terms of execution time and cost and transfer them
to business processes; and (ii) we extensively evaluate the existing solutions.
Our results shed light on the merits of each heuristic and show that our new
heuristics can yield significant benefits.
