A Deep Learning Approach to Minimize Retrieval Time in Shuttle-Based Storage Systems

Paul Courtin, Paul Courtin, Jean-Baptiste Fasquel, Mehdi Lhommeau, Axel Grimault

2025

Abstract

Improvement of picking performances in automated warehouse is influenced by the assignment of articles to storage locations. This problem is known as the Storage Location Assignment Problem (SLAP). In this paper, we present a deep learning method to assign articles to storage locations inside a shuttles-based storage and retrieval system (SBS/RS). We introduce the architecture of our a LSTM-based model and the public dataset used. Finally, we compare the retrieval time of articles provided by our model against other allocation methods.

Paper Citation

in Harvard Style

Courtin P., Fasquel J., Lhommeau M. and Grimault A. (2025). A Deep Learning Approach to Minimize Retrieval Time in Shuttle-Based Storage Systems. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1040-1047. DOI: 10.5220/0013255300003890

in Bibtex Style

@conference{icaart25,
author={Paul Courtin and Jean-Baptiste Fasquel and Mehdi Lhommeau and Axel Grimault},
title={A Deep Learning Approach to Minimize Retrieval Time in Shuttle-Based Storage Systems},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1040-1047},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013255300003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - A Deep Learning Approach to Minimize Retrieval Time in Shuttle-Based Storage Systems
SN - 978-989-758-737-5
AU - Courtin P.
AU - Fasquel J.
AU - Lhommeau M.
AU - Grimault A.
PY - 2025
SP - 1040
EP - 1047
DO - 10.5220/0013255300003890
PB - SciTePress