Abstract
Efficient warehouse management relies heavily on aligning storage policies with operational strategies to minimise travel distances and improve order-picking efficiency. While storage location assignment policies provide structured frameworks for inventory organization, their impact on picking route optimisation based on real-world settings remains underexplored. This study reviews the main storage policies reported in the literature and evaluates the performance of four storage policies - Random, Class-Based, Dedicated, and Hybrid - within a dynamic warehouse environment of a shoe manufacturing company. The analysis identifies their effects on travel distances, variability, and overall efficiency by systematically comparing these policies. The results demonstrate that Dedicated and Hybrid policies consistently outperform others, with the Hybrid policy showing particular promise in environments with high product variability due to its balance between flexibility and structure. The findings offer practical insights for addressing the storage location assignment problem (SLAP) and highlight the value of integrating storage strategies to enhance warehouse operations. This research contributes to the literature by offering a comprehensive evaluation of storage policies and emphasising their role in addressing the operational challenges of modern warehouses.
| Original language | English |
|---|---|
| Pages (from-to) | 2485-2490 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 59 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 1 Jul 2025 |
| Event | 11th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2025 - Trondheim, Norway Duration: 30 Jun 2025 → 3 Jul 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
!!!Keywords
- Genetic Algorithms
- Hybrid Storage Strategy
- Order-picking optimisation
- Storage Policies
- Warehouse Management
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