ENGLISH
La vitrine de diffusion des publications et contributions des chercheurs de l'ÉTS
RECHERCHER

Order picking dataset from a warehouse of a footwear manufacturing company

de Assis, Rodrigo Furlan, de Paula Ferreira, William et Ouhimmou, Mustapha. 2025. « Order picking dataset from a warehouse of a footwear manufacturing company ». Data in Brief, vol. 61.

[thumbnail of dePaula-Ferreira-W-2025-31194.pdf]
Prévisualisation
PDF
dePaula-Ferreira-W-2025-31194.pdf - Version publiée
Licence d'utilisation : Creative Commons CC BY-NC.

Télécharger (972kB) | Prévisualisation

Résumé

This dataset originates from a real-world footwear manufacturing warehouse and provides a comprehensive foundation for benchmarking research in warehouse order-picking operations. Data was collected via SQL queries on the company’s Warehouse Management System (WMS), resulting in diverse formats such as CSV files, CAD layouts, and Python scripts. The dataset includes geometric representations of the warehouse layout, with Cartesian-mapped storage locations, aisles, and central depots, detailed product classifications, storage positions, picking wave information, and routing paths. It supports evaluating various storage strategies, including Random, Class-Based, Dedicated, and Hybrid configurations, enabling the analysis of their impact on order-picking efficiency. Temporal data captures operational trends, including timestamps and operator-specific performance, offering insights into workflow efficiency and workload balancing. Anonymization and randomization techniques were applied while retaining realistic operational patterns to preserve confidentiality. This dataset is highly versatile and suitable for developing optimization algorithms for picker routing, order batching, wave generation, and intralogistics, as well as for advancing automation and robotics research through navigation-specific data for autonomous guided vehicles (AGVs) and robotic systems. This dataset significantly contributes to warehouse logistics research and operational optimization by supporting a wide range of applications.

Type de document: Article publié dans une revue, révisé par les pairs
Professeur:
Professeur
de Paula Ferreira, William
Ouhimmou, Mustapha
Affiliation: Génie des systèmes, Génie des systèmes
Date de dépôt: 30 juill. 2025 13:35
Dernière modification: 10 sept. 2025 20:10
URI: https://espace2.etsmtl.ca/id/eprint/31194

Actions (Authentification requise)

Dernière vérification avant le dépôt Dernière vérification avant le dépôt