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Authors: Wilfried Elmenreich 1 ; Alexander Schnabl 1 and Melanie Schranz 2

Affiliations: 1 Institute of Networked and Embedded Systems, Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria ; 2 Lakeside Labs, Klagenfurt, Austria

Keyword(s): Production Scheduling, Job-shop Scheduling, Artificial Hormone Systems, Self-organizing Systems, Swarm Systems.

Abstract: This paper presents a model for supporting a production scheduling system with an artificial hormone algorithm. The system consists of lots that have to undergo a number of processing steps on different machines. The processing steps for a lot are formalized in a recipe assigned to the lot type. Since the steps in the recipe have to be processed in order, the given system allows choice only in the context of selecting a particular machine for the next step and in changing the processing order of waiting lots at a machine. Optimization of such a job-shop scheduling system is an NP-hard problem. In the approach proposed by this paper, artificial hormone systems are used to express the urgency of a lot and the need for new lots at a machine type, thus providing a system using local information for optimization. Results indicate that the artificial hormone system provides an improvement of around 5% over a First Come-First Serve approach.

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Paper citation in several formats:
Elmenreich, W.; Schnabl, A. and Schranz, M. (2021). An Artificial Hormone-based Algorithm for Production Scheduling from the Bottom-up. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 296-303. DOI: 10.5220/0010243902960303

@conference{icaart21,
author={Wilfried Elmenreich. and Alexander Schnabl. and Melanie Schranz.},
title={An Artificial Hormone-based Algorithm for Production Scheduling from the Bottom-up},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2021},
pages={296-303},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010243902960303},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - An Artificial Hormone-based Algorithm for Production Scheduling from the Bottom-up
SN - 978-989-758-484-8
IS - 2184-433X
AU - Elmenreich, W.
AU - Schnabl, A.
AU - Schranz, M.
PY - 2021
SP - 296
EP - 303
DO - 10.5220/0010243902960303
PB - SciTePress

- Science and Technology Publications, Lda.
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