Detail publikace
Comparing Surrogate-Assisted Evolutionary Algorithms on Optimization of a Simulation Model for Resource Planning Task for Hospitals
KŮDELA, J. DOBROVSKÝ, L. SHEHADEH, M. HŮLKA, T. MATOUŠEK, R.
Anglický název
Comparing Surrogate-Assisted Evolutionary Algorithms on Optimization of a Simulation Model for Resource Planning Task for Hospitals
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
en
Originální abstrakt
Surrogate-assisted evolutionary algorithms (SAEAs) are currently among the most widely researched techniques for their capability to solve expensive real-world optimization problems. The development of these techniques and their bench-marking with other methods still relies almost exclusively on artificially created problems. In this paper, we use a real-world problem of optimizing the parameters of a hospital resource planning tool to compare the performance of nine state-of-the-art single-objective SAEAs. We find that there are significant differences between the performance of the compared methods on the selected instances, making the problems suitable for benchmarking SAEAs.
Anglický abstrakt
Surrogate-assisted evolutionary algorithms (SAEAs) are currently among the most widely researched techniques for their capability to solve expensive real-world optimization problems. The development of these techniques and their bench-marking with other methods still relies almost exclusively on artificially created problems. In this paper, we use a real-world problem of optimizing the parameters of a hospital resource planning tool to compare the performance of nine state-of-the-art single-objective SAEAs. We find that there are significant differences between the performance of the compared methods on the selected instances, making the problems suitable for benchmarking SAEAs.
Klíčová slova anglicky
Expensive optimization; evolutionary algorithm; surrogate model; resource planning; benchmarking; healthcare
Vydáno
08.08.2024
Nakladatel
IEEE
ISBN
979-8-3503-0836-5
Kniha
2024 IEEE Congress on Evolutionary Computation (CEC)
Počet stran
8
BIBTEX
@inproceedings{BUT196903,
author="Jakub {Kůdela} and Ladislav {Dobrovský} and Mhd Ali {Shehadeh} and Tomáš {Hůlka} and Radomil {Matoušek},
title="Comparing Surrogate-Assisted Evolutionary Algorithms on Optimization of a Simulation Model for Resource Planning Task for Hospitals",
booktitle="2024 IEEE Congress on Evolutionary Computation (CEC)",
year="2024",
month="August",
publisher="IEEE",
isbn="979-8-3503-0836-5"
}