Research on an Automatic Goods Zone Allocation Model for Multi-Story Warehouses Based on Multi-Dimensional Parameter Control and Machine Vision Applications
- DOI
- 10.2991/978-94-6463-916-2_40How to use a DOI?
- Keywords
- Outbound frequency; daily outbound volume; inventory-sales ratio; automatic zone allocation; machine vision
- Abstract
To optimize the internal distribution of goods and achieve automatic zone allocation for fast-moving consumer goods during the inbound process, thereby reducing internal handling costs, this study introduces control parameters related to daily outbound volume, outbound frequency, and inventory-sales ratio. The inventory-sales ratio at the building and floor levels is used as the basis for determining floor allocation, while daily outbound volume and brand relevance serve as the criteria for specific location selection. By integrating machine vision to collect vehicle information, a model for automatic zone allocation in multi-story warehouses is established. Empirical results show that: (1) 100% automatic zone allocation is achieved upon goods receipt; (2) internal goods transfer volume is reduced by 65.29%. The findings demonstrate the effectiveness of the proposed model in multi-story warehouse applications.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Bin Ye AU - Nan Zhou AU - Lingfei Zhu AU - Lin Chen AU - Shanjie Yang AU - Chao Yu PY - 2025 DA - 2025/12/22 TI - Research on an Automatic Goods Zone Allocation Model for Multi-Story Warehouses Based on Multi-Dimensional Parameter Control and Machine Vision Applications BT - Proceedings of the 2025 4th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2025) PB - Atlantis Press SP - 361 EP - 371 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-916-2_40 DO - 10.2991/978-94-6463-916-2_40 ID - Ye2025 ER -