Grupo Alarcos · Book chapter · 2021
A Novel Approach for Business Process Model Matching Using Genetic Algorithms
Mostefai Abdelkader, Ignacio García Rodríguez de Guzmán
This paper formulates the process model matching problem as an optimization problem and presents a heuristic approach based on genetic algorithms for computing a good enough alignment. An alignment is a set of not overlapping correspondences (i.e., pairs) between two process models(i.e., BP) and each correspondence is a pair of two sets of activities that represent the same behavior. The first set belongs to a source BP and the second set to a target BP. The proposed approach computes the solution by searching, over all possible alignments, the one that maximizes the intra-pairs cohesion while minimizing inter-pairs coupling. Cohesion of pairs and coupling between them is assessed using a proposed heuristic that combines syntactic and semantic similarity metrics. The proposed approach was evaluated on three well-known datasets. The results of the experiment showed that the approach has the potential to match business process models effectively.