(287c) Using Knowledge Management for the Optimal Integration of Hierarchical Decision Making

Ontologies have been recognized as suitable tools to build complex semantic models. They improve
information sharing and communication among the different hierarchical levels and functionalities of the
enterprise. They also provide the capability of automatically instancing holistic mathematical models of
the enterprise from transactional systems, thus facilitating the use of analytic tools in business decision
making and practice (Muñoz et al, 2013a). Recently, a semantic representation of those elements of the
enterprise (i.e., decisions, parameters, constraints, performance indicators) which are included in
optimization models has been developed to additionally capture their meaning in terms of the
mathematical language. By doing so, decision makers are given the ability of modifying the analytical
models by means of the ontological framework according to new circumstances (constraints, variables),
thus providing a higher flexibility for model building (Muñoz et al, 2013b).
In this work, we further exploit this capability in order to address the optimal integration of hierarchical
decision levels. Specifically, we aim at solving the supply chain management problem represented in the
ontology by means of rigorous mathematical optimization emphasizing the requirement of long term
horizon representation. Once strategic solutions are obtained, results are represented within the
ontological framework. Such information is used by the planning decision level, which further optimizes its
function. Next, results from planning are further represented in the ontological model. Finally, the batch
control function further manages the information gathered from the optimization results in the ontology,
and applies the batch control recipes resulting from the planning function.