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Research on congestion rate of classified storage narrow channel picking system for IoT security

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Abstract

The smart mobile Internet of Things (IoT) is a novel paradigm that is rapidly gaining ground in the field of modern wireless telecommunications. Picking operations are the key link in an entire warehousing operation, and congestion problems significantly contribute to managers’ decisions regarding the warehousing layout, the storage strategy, and the number of pickers. In this paper, the discrete Markov method is used to study the problem of picking congestion in a narrow-aisle double picking system with a traditional layout, an S-type picking path and a classified storage strategy. First, congestion models are constructed when the picker picks one item with a picking speed that is equal to the walking speed and when the picker picks multiple items on one picking surface under a picking speed that is very different from the walking speed. A sensitivity analysis involving parameter changes was carried out. Second, the paper compares and analyzes situations in which the picking speed is equal to the walking speed and in which there is a large difference between the picking speed and the walking speed and determines the impact of the picking speed, the number of goods picked on a picking surface, the differentiated classified storage strategy, and the number of picking surfaces on the picking congestion rate. The effectiveness of the mathematical model was verified by a MATLAB simulation, and the exploration and discovery for subsequent research were performed.

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Acknowledgements

This study is supported by the key project of Beijing Social Science Foundation “strategic research on improving the service quality of capital logistics based on big data technology” (18GLA009), the National Nature Science Foundation of China “Research on the warehouse picking system blocking influence factors and combined control strategy” (No.71501015), and the Beijing Great Wall scholars program (No. CIT & TCD20170317). 

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Authors and Affiliations

  1. School of Information, Beijing Wuzi University, Beijing, China

    Li Zhou, Xiaxia Niu, Shengli Zhao & Xiaoqing Zhao

  2. School of Internet of Things and Software Technology, Wuxi Vocational College of Science and Technology, Wuxi, China

    Ning Cao

  3. School of Computer Science and Technology, Harbin Institute of Technology at Weihai, Weihai, China

    Jianrui Ding

  4. University College Dublin, Dublin, Ireland

    Ruichao Wang

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  1. Li Zhou
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Correspondence to Ning Cao.

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Zhou, L., Niu, X., Zhao, S. et al. Research on congestion rate of classified storage narrow channel picking system for IoT security. Wireless Netw 30, 6307–6323 (2024). https://doi.org/10.1007/s11276-020-02372-6

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  • DOI: https://doi.org/10.1007/s11276-020-02372-6

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