A Concept for Optimal Warehouse Allocation Using Contextual Multi-Arm Bandits

Giulia Siciliano, David Braun, Korbinian Zöls, Johannes Fottner

2023

Abstract

This paper presents and demonstrates a conceptual approach for applying the Linear Upper Confidence Bound algorithm, a contextual Multi-arm Bandit agent, for optimal warehouse storage allocation. To minimize the cost of picking customer orders, an agent is trained to identify optimal storage locations for incoming products based on information about remaining storage capacity, product type and packaging, turnover frequency, and product synergy. To facilitate the decision-making of the agent for large-scale warehouses, the action selection is performed for a low-dimensional, spatially-clustered representation of the warehouse. The capability of the agent to suggest storage locations for incoming products is demonstrated for an exemplary warehouse with 4,650 storage locations and 30 product types. In the case study considered, the performance of the agent matches that of a conventional ABC-analysis-based allocation strategy, while outperforming it in regards to exploiting inter-categorical product synergies.

Paper Citation

in Harvard Style

Siciliano G., Braun D., Zöls K. and Fottner J. (2023). A Concept for Optimal Warehouse Allocation Using Contextual Multi-Arm Bandits. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-648-4, SciTePress, pages 460-467. DOI: 10.5220/0011839700003467

in Bibtex Style

@conference{iceis23,
author={Giulia Siciliano and David Braun and Korbinian Zöls and Johannes Fottner},
title={A Concept for Optimal Warehouse Allocation Using Contextual Multi-Arm Bandits},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2023},
pages={460-467},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011839700003467},
isbn={978-989-758-648-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Concept for Optimal Warehouse Allocation Using Contextual Multi-Arm Bandits
SN - 978-989-758-648-4
AU - Siciliano G.
AU - Braun D.
AU - Zöls K.
AU - Fottner J.
PY - 2023
SP - 460
EP - 467
DO - 10.5220/0011839700003467
PB - SciTePress