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Reliability Analysis and Optimization of Cold Chain Distribution System for Fresh Agricultural Products

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  • Jinghan Zhang

    (Graduate School of Logistics, Inha University, Incheon 22212, Korea
    School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Wujun Cao

    (School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China)

  • Minyoung Park

    (Graduate School of Logistics, Inha University, Incheon 22212, Korea)

Abstract

In recent years, with the Chinese government’s emphasis on the development of the cold chain logistics market for fresh agricultural products, the rapid development of agricultural cold chain logistics has been promoted in many aspects. However, in the circulation of fresh agricultural products, there is still a serious problem of “broken chain” leading to a high corrosion rate. Therefore, this research has analyzed the uncertain factors affecting the cold chain distribution system based on fault tree model, and then transform it into Bayesian network to evaluate the reliability of the cold chain distribution system for fresh agricultural product, and identify the key factors affecting the reliability of the cold chain distribution system through calculated probability importance of each node. Then we have constructed nonlinear equations with the limit of the cost, based on reliability allocation method to improve the system reliability. Numerical examples are given to validate the proposed models. The optimization result shows that higher reliability value assigned to the factors with high probability importance is more conducive to the improvement of system reliability.

Suggested Citation

  • Jinghan Zhang & Wujun Cao & Minyoung Park, 2019. "Reliability Analysis and Optimization of Cold Chain Distribution System for Fresh Agricultural Products," Sustainability, MDPI, vol. 11(13), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:13:p:3618-:d:244737
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    References listed on IDEAS

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    1. Athakorn Kengpol & Sopida Tuammee, 2016. "The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: an empirical study," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1020-1038, February.
    2. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    3. Andrea Gallo & Riccardo Accorsi & Giulia Baruffaldi & Riccardo Manzini, 2017. "Designing Sustainable Cold Chains for Long-Range Food Distribution: Energy-Effective Corridors on the Silk Road Belt," Sustainability, MDPI, vol. 9(11), pages 1-20, November.
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    Cited by:

    1. Han Yan & Min-Ju Song & Hee-Yong Lee, 2021. "A Systematic Review of Factors Affecting Food Loss and Waste and Sustainable Mitigation Strategies: A Logistics Service Providers’ Perspective," Sustainability, MDPI, vol. 13(20), pages 1-20, October.
    2. Xuemei Fan & Ziyue Nan & Yuanhang Ma & Yingdan Zhang & Fei Han, 2021. "Research on the Spatio-Temporal Impacts of Environmental Factors on the Fresh Agricultural Product Supply Chain and the Spatial Differentiation Issue—An Empirical Research on 31 Chinese Provinces," IJERPH, MDPI, vol. 18(22), pages 1-26, November.
    3. Minghua Dai & Guanwei Wang & Jiaqiu Wang & Yuhan Gao & Quanzhen Lu, 2023. "Study of the Spatial Spillover Effects of the Efficiency of Agricultural Product Circulation in Provinces along the Belt and Road under the Green Total Factor Productivity Framework," Sustainability, MDPI, vol. 15(16), pages 1-20, August.
    4. Kai Pan & Hui Liu & Xiaoqing Gou & Rui Huang & Dong Ye & Haining Wang & Adam Glowacz & Jie Kong, 2022. "Towards a Systematic Description of Fault Tree Analysis Studies Using Informetric Mapping," Sustainability, MDPI, vol. 14(18), pages 1-28, September.

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