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An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles

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  • He-Yau Kang
  • Amy H.I. Lee
  • Chien-Wei Wu
  • Cheng-Han Lee

Abstract

How to improve competitive edges to meet rapidly changing market environment and dynamic customer needs is critical for the survival and success of firms these days. A good supply chain and inventory management is a necessity in the intensive competitive market. This paper considers a dynamic-demand joint replenishment problem with multiple vehicle routing. The problem is first formulated as a mixed integer programming model with an objective to minimise total costs, which include ordering cost, purchase cost, production cost, transportation cost and holding cost, under a prerequisite that inventory shortage is prohibited in the system. A particle swarm optimisation model is proposed next to solve large-scale problems which are computationally difficult. A case study of a touch panel manufacturer is presented to examine the practicality of the models.

Suggested Citation

  • He-Yau Kang & Amy H.I. Lee & Chien-Wei Wu & Cheng-Han Lee, 2017. "An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1065-1084, February.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:1065-1084
    DOI: 10.1080/00207543.2016.1218564
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    References listed on IDEAS

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    Cited by:

    1. Wang, Min & Zhao, Lindu & Herty, Michael, 2019. "Joint replenishment and carbon trading in fresh food supply chains," European Journal of Operational Research, Elsevier, vol. 277(2), pages 561-573.
    2. Baller, Annelieke C. & Dabia, Said & Dullaert, Wout E.H. & Vigo, Daniele, 2019. "The Dynamic-Demand Joint Replenishment Problem with Approximated Transportation Costs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1013-1033.
    3. Avelina Alejo-Reyes & Erik Cuevas & Alma Rodríguez & Abraham Mendoza & Elias Olivares-Benitez, 2020. "An Improved Grey Wolf Optimizer for a Supplier Selection and Order Quantity Allocation Problem," Mathematics, MDPI, vol. 8(9), pages 1-24, August.
    4. Chen, Kuen-Suan & Wang, Ching-Hsin & Tan, Kim-Hua, 2019. "Developing a fuzzy green supplier selection model using six sigma quality indices," International Journal of Production Economics, Elsevier, vol. 212(C), pages 1-7.
    5. Amy H. I. Lee & He-Yau Kang & Sih-Jie Ye & Wan-Yu Wu, 2018. "An Integrated Approach for Sustainable Supply Chain Management with Replenishment, Transportation, and Production Decisions," Sustainability, MDPI, vol. 10(11), pages 1-21, October.

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