Year: 2025
Type: conference-paper
Abstract: As computational resources get cheaper and more convenient, largely through cloud technologies, the general trend is to solve larger simulation optimisation problems with more complex/realistic simulation models, sometimes in an exhaustive manner. This is despite the need for the computing sector and thus the simulation sector to reduce its carbon emissions. This paper advocates for using simpler models to aid the optimisation, particularly in queueing network problems, where many analytical models have been developed and system behaviours can make simulation optimisation more difficult. We focus on Jackson Networks for multi-fidelity optimisation of a server allocation problem, and set up a series of experiments to examine how well these models can aid simulation optimisation.
DOI: 10.36819/sw25.028
Authors: Luke Rhodes-Leader, Yu-Ting Lin
Institution: Lancaster University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4408658472