Bottom-up Job Shop Scheduling with Swarm Intelligence in Large Production Plants

M. Schranz, M. Umlauft, W. Elmenreich

2021

Abstract

In production plants organized by the job shop principle, the factory-wide scheduling problem is NP-hard and can become extremely large. Traditional optimization methods like linear optimization reach their limits in these settings due to excessive computation time. Therefore, we propose this industrial setting as a novel field of application for swarm intelligence using bottom-up algorithms that do not require the infeasible calculation of an overall solution but depend only on local information. We consider the example of the semiconductor industry producing logic and power integrated circuits where a diverse range of highly specialized but low volume products are fabricated in the same plant. This paper shows how to select and model swarm members, swarms, and their interactions for use in real-world production plants. There are multiple possibilities for the modeling of the agents: a swarm member could be a single machine or a set of machines (workcenter), a product or group of products of the same/similar type, or a more abstract agent like a process. In particular, we consider criteria for selecting appropriate swarm members and potential candidate swarm algorithms inspired by hormones and ants.

Paper Citation

in Harvard Style

Schranz M., Umlauft M. and Elmenreich W. (2021). Bottom-up Job Shop Scheduling with Swarm Intelligence in Large Production Plants. In Proceedings of the 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-528-9, pages 327-334. DOI: 10.5220/0010551603270334

in Bibtex Style

@conference{simultech21,
author={M. Schranz and M. Umlauft and W. Elmenreich},
title={Bottom-up Job Shop Scheduling with Swarm Intelligence in Large Production Plants},
booktitle={Proceedings of the 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2021},
pages={327-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010551603270334},
isbn={978-989-758-528-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Bottom-up Job Shop Scheduling with Swarm Intelligence in Large Production Plants
SN - 978-989-758-528-9
AU - Schranz M.
AU - Umlauft M.
AU - Elmenreich W.
PY - 2021
SP - 327
EP - 334
DO - 10.5220/0010551603270334