A structural model comparison for finding the best performing models in a collection

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Abstract

An improvement or redesign of a process often starts by modifying the model supporting the process. Analysis techniques, like simulation, can be used to evaluate alternatives. However, even a small number of design choices may lead to an explosion of models that need to be explored to find the optimal models for said process. If the exploration depends on simulation, it often becomes infeasible to simulate every model. Therefore, for throughput time, we define a notion of monotonicity to reduce the number of models required to be simulated whilst the optimal models are still found.

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Schunselaar, D. M. M., Verbeek, H. M. W., Reijers, H. A., & van der Aalst, W. M. P. (2015). A structural model comparison for finding the best performing models in a collection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9253, pp. 180–188). Springer Verlag. https://doi.org/10.1007/978-3-319-23063-4_12

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