Hospital simulation model optimisation with a random ReLU expansion surrogate model
Presented at the Genetic and Evolutionary Computation Conference (July 2021), Virtual, Online
The industrial challenge of the GECCO 2021 conference is an expensive optimisation problem, where the parameters of a hospital simulation model need to be tuned to optimality. We show how a surrogate-based optimisation framework, with a random ReLU expansion as the surrogate model, outperforms other methods such as Bayesian optimisation, Hyperopt, and random search on this problem.
|Genetic and Evolutionary Computation Conference|
|Organisation||Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands|
Bliek, L, Guijt, A, & Karlsson, R. (2021). Hospital simulation model optimisation with a random ReLU expansion surrogate model. In GECCO 2021 Proceedings (pp. 13–14). doi:10.1145/3449726.3463279