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Research on an Automatic Goods Zone Allocation Model for Multi-Story Warehouses Based on Multi-Dimensional Parameter Control and Machine Vision Applications

In: Proceedings of the 2025 4th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2025)

Author

Listed:
  • Bin Ye

    (China Tobacco Zhejiang Industrial Co., Ltd)

  • Nan Zhou

    (China Tobacco Yunnan Industrial Co., Ltd)

  • Lingfei Zhu

    (China Tobacco Zhejiang Industrial Co., Ltd)

  • Lin Chen

    (China Tobacco Zhejiang Industrial Co., Ltd)

  • Shanjie Yang

    (China Tobacco Zhejiang Industrial Co., Ltd)

  • Chao Yu

    (China Tobacco Zhejiang Industrial Co., Ltd)

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.

Suggested Citation

  • Bin Ye & Nan Zhou & Lingfei Zhu & Lin Chen & Shanjie Yang & Chao Yu, 2025. "Research on an Automatic Goods Zone Allocation Model for Multi-Story Warehouses Based on Multi-Dimensional Parameter Control and Machine Vision Applications," Advances in Economics, Business and Management Research, in: Qihui Chen & Nazrul Islam & Zulkiflee bin Mohamed & Yahua Xu (ed.), Proceedings of the 2025 4th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2025), pages 361-371, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-916-2_40
    DOI: 10.2991/978-94-6463-916-2_40
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