Process-aware information systems (PAISs) are increasingly used to provide flexible
support for business processes. The support given through a PAIS is greatly enhanced
when it is able to provide accurate time predictions which is typically a very challenging
task. Predictions should be (1) multi-dimensional and (2) not based on a single process
instance. Furthermore, the prediction system should be able to (3) adapt to changing
circumstances and (4) deal with multi-perspective declarative languages (e.g., models
which consider time, resource, data and control flow perspectives). In this work, a novel
approach for generating time predictions considering the aforementioned characteristics is
proposed. For this, first, a multi-perspective constraint-based language is used to model the
scenario. Thereafter, an optimized enactment plan (representing a potential execution
alternative) is generated from such a model considering the current execution state of the
process instances. Finally, pre-dictions are performed by evaluating a desired function over
this enactment plan. To evaluate the applicability of our approach in practical settings we
apply it to a real process scenario. Despite the high complexity of the considered problems,
results indicate that our approach produces a satisfactory number of good predictions in a
reasonable time.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71618-
