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Joint Decisions of Inventory Optimization and Order Allocation for Omni-Channel Multi-Echelon Distribution Network

Author

Listed:
  • Ting Qu

    (GBA and B&R International Joint Research Center for Smart Logistics, Jinan University, Zhuhai 519070, China
    School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China
    Institute of Physical Internet, Jinan University, Zhuhai 519070, China)

  • Tianxiang Huang

    (School of Management, Jinan University, Guangzhou 510632, China)

  • Duxian Nie

    (College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China)

  • Yelin Fu

    (School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China)

  • Lin Ma

    (School of Management, Jinan University, Guangzhou 510632, China)

  • George Q. Huang

    (Department Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China)

Abstract

Firms with omni-channel multi-echelon distribution networks (OMDC) integrate all of their sale channels and distribution echelons to achieve an effective matching of multi-type orders and a shared inventory. However, the high operational cost caused by insufficient use of inventory resources and unreasonable order allocation restricts the sustainable development of firms. To this end, the joint decisions of inventory optimization (IO) and order allocation (OA) are explored to achieve cost-efficient and sustainable omni-channel operations. Specifically, from the perspective of IO, an inventory integrated policy is proposed for online and offline inventory sharing within nodes and lateral transshipment between nodes; from the aspect of OA, an order allocation mechanism is designed for the minimum cost under the influence of multiple factors (inventory replenishment, holding, order delivery distance and time) among different echelon nodes. A joint optimization model of an inventory and orders is therefore developed and is subsequently solved using the Genetic Algorithm (GA). Results obtained show that the proposed strategy has a better performance with regards to operational cost and customer service level and is also more sustainable than alternative strategies. The proposed joint strategy provides a relatively novel approach to realize flexible and sustainable omni-channel distribution systems.

Suggested Citation

  • Ting Qu & Tianxiang Huang & Duxian Nie & Yelin Fu & Lin Ma & George Q. Huang, 2022. "Joint Decisions of Inventory Optimization and Order Allocation for Omni-Channel Multi-Echelon Distribution Network," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:5903-:d:814613
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