Metaheuristic Optimization for Automated Business Process Discovery
A Augusto, M Dumas, M La Rosa
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Springer | Published : 2019
The problem of automated discovery of process models from event logs has been intensely investigated in the past two decades, leading to a range of approaches that strike various trade-offs between accuracy, model complexity, and execution time. A few studies have suggested that the accuracy of automated process discovery approaches can be enhanced by using metaheuristic optimization. However, these studies have remained at the level of proposals without validation on real-life logs or they have only considered one metaheuristics in isolation. In this setting, this paper studies the following question: To what extent can the accuracy of automated process discovery approaches be improved by a..View full abstract
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Awarded by Australian Research Council
Awarded by Estonian Research Council
We thank Raffaele Conforti for his input to an earlier version of this paper. This research is partly funded by the Australian Research Council (DP180102839) and the Estonian Research Council (IUT20-55).