Tutorial: Artificial Neural Networks for Discrete-Event Simulation
This advanced tutorial explores some recent applications of artificial neural networks (ANNs) to stochastic discrete-event simulation (DES). We first review some basic concepts and then give examples of how ANNs are being used in the context of DES to facilitate simulation input modeling, random variate generation, simulation metamodeling, optimization via simulation, and more. Combining ANNs and DES allows exploitation of the deep domain knowledge embodied in simulation models while simultaneously leveraging the ability of modern ML techniques to capture complex patterns and relationships in data.
Authors
- Peter J. Haas (ORCID: https://orcid.org/0000-0001-5694-3065)
Institutions
- Amherst College (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/wsc63780.2024.10838940
- Citations
- 4
- Primary Topic
- Simulation Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.96