Surrogate-based optimisation for a hospital simulation scenario using pairwise classifiers
Author:
Affiliation:
1. Universidad Politécnica de Madrid, Madrid, Spain
2. Lurtis Ltd., Oxford, UK
Funder
Spanish Ministry of Science
Comunidad de Madrid
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3449726.3463283
Reference7 articles.
1. Thomas Bartz-Beielstein Frederik Rehbach Olaf Mersmann and Eva Bartz. 2020. Hospital capacity planning using discrete event simulation under special consideration of the COVID-19 pandemic. arXiv:2012.07188 Thomas Bartz-Beielstein Frederik Rehbach Olaf Mersmann and Eva Bartz. 2020. Hospital capacity planning using discrete event simulation under special consideration of the COVID-19 pandemic. arXiv:2012.07188
2. Classification And Regression Trees
3. Greedy function approximation: A gradient boosting machine.
4. Surrogate-based optimization. In Real-world applications of genetic algorithms. IntechOpen, Rijeka;Han Zhong-Hua;Chapter,2012
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1. Sequential Hybridization of Online Surrogate Models for Continuous Optimization;Proceedings of the Companion Conference on Genetic and Evolutionary Computation;2023-07-15
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