Semantic interoperability represents the ability of two or more systems to automatically interpret the information exchanged meaningfully in order to produce useful results. Currently, the best recognized technology for achieving a specification of meaning is represented by ontologies. However, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with discrepancies and heterogeneities. As a consequence, an ontology alignment process is necessary for bridging this gap and achieving a full communication understanding across different software components. This paper uses a synergetic approach, based on the integration of collaborative agents and parallel memetic algorithms, for efficiently aligning ontologies and, consequently, solving the semantic heterogeneity problem. As shown by a statistical procedure, our approach yields high performance in terms of the ratio between alignment quality and computational effort with respect to conventional evolutionary approaches for ontology alignment. © 2013 IEEE