In the field of complex problem optimization with metaheuristics, semantics has been used
for modeling different aspects, such as: problem characterization, parameters, decision-
maker's preferences, or algorithms. However, there is a lack of approaches where
ontologies are applied in a direct way into the optimization process, with the aim of
enhancing it by allowing the systematic incorporation of additional domain knowledge. This
is due to the high level of abstraction of ontologies, which makes them difficult to be mapped …