Conference Proceedings

An evolutionary technique to approximate multiple optimal alignments

F Taymouri, J Carmona, M Weske, M Montali, I Weber, J vom Brocke

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Springer Nature Switzerland AG | Published : 2018

Abstract

© Springer Nature Switzerland AG 2018. The alignment of observed and modeled behavior is an essential aid for organizations, since it opens the door for root-cause analysis and enhancement of processes. The state-of-the-art technique for computing alignments has exponential time and space complexity, hindering its applicability for medium and large instances. Moreover, the fact that there may be multiple optimal alignments is perceived as a negative situation, while in reality it may provide a more comprehensive picture of the model’s explanation of observed behavior, from which other techniques may benefit. This paper presents a novel evolutionary technique for approximating multiple optima..

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