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Optimal Logistics Control of an Omnichannel Supply Chain

Author

Listed:
  • Yufeng Zhuang

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Ningxi Zhang

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Song Wang

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Yanzhu Hu

    (School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Abstract

This paper aims to find the best way to control logistics in an omnichannel supply chain (OSC). For this purpose, two steps of work were carried out around case-based reasoning (CBR). In the first step, the combined feedback which proved stability was selected to control logistics in the single node, while the variational method and the virtual siphon were combined to determine the optimal control curve. There is a linear part and a nonlinear part in the combined feedback. The new method of storing data mode is “data turning to picture”. In the second step, image features were extracted by the hybrid method of SURF-GoogLeNet and used for case matching via the grey cloud method. SURF-GoogLeNet was firstly used to update the weight proportion of the defect points in the whole image via the speeded up robust features (SURF) method and secondly to self-extract features using the GoogLeNet method. Finally, the effectiveness of the proposed methods was verified through experiments. The research findings shed new light on the management of supply chains.

Suggested Citation

  • Yufeng Zhuang & Ningxi Zhang & Song Wang & Yanzhu Hu, 2019. "Optimal Logistics Control of an Omnichannel Supply Chain," Sustainability, MDPI, vol. 11(21), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:6014-:d:281492
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    References listed on IDEAS

    as
    1. Du, Shaofu & Wang, Li & Hu, Li, 2019. "Omnichannel management with consumer disappointment aversion," International Journal of Production Economics, Elsevier, vol. 215(C), pages 84-101.
    2. Gupta, Vishal Kumar & Ting, Q.U. & Tiwari, Manoj Kumar, 2019. "Multi-period price optimization problem for omnichannel retailers accounting for customer heterogeneity," International Journal of Production Economics, Elsevier, vol. 212(C), pages 155-167.
    3. Hesham K. Alfares & Ahmed M. Attia, 2017. "A supply chain model with vendor-managed inventory, consignment, and quality inspection errors," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5706-5727, October.
    4. Jack SK Chang & Carolyn Chang & Min Shi, 2015. "A market-based martingale valuation approach to optimum inventory control in a doubly stochastic jump-diffusion economy," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 405-420, March.
    Full references (including those not matched with items on IDEAS)

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