Using NetLogo to Simulate Large Production Plants: Simulation Performance: A Case Study

M. Umlauft, M. Schranz

2024

Abstract

NetLogo is a well-known agent-based modeling and simulation platform. While it is very popular in education, it is still often perceived as having bad performance for large models, which is due to performance related issues in early implementations. We show that over time, a quite large number of scientific papers have been published using NetLogo and measure its performance on a common laptop a researcher or student might have as a personal machine. We use a NetLogo model with about 2500 lines of code and up to 10000 agents to perform our measurements and show that even with such an underpowered machine, with current versions of NetLogo it is quite possible to run simulations of larger models in reasonable simulation time.

Paper Citation

in Harvard Style

Umlauft M. and Schranz M. (2024). Using NetLogo to Simulate Large Production Plants: Simulation Performance: A Case Study. In Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-708-5, SciTePress, pages 297-304. DOI: 10.5220/0012768800003758

in Bibtex Style

@conference{simultech24,
author={M. Umlauft and M. Schranz},
title={Using NetLogo to Simulate Large Production Plants: Simulation Performance: A Case Study},
booktitle={Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2024},
pages={297-304},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012768800003758},
isbn={978-989-758-708-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - Using NetLogo to Simulate Large Production Plants: Simulation Performance: A Case Study
SN - 978-989-758-708-5
AU - Umlauft M.
AU - Schranz M.
PY - 2024
SP - 297
EP - 304
DO - 10.5220/0012768800003758
PB - SciTePress