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Research on Green Technology Path of Cold-Chain Distribution of Fresh Products Based on Sustainable Development Goals

Author

Listed:
  • Lei Zhou

    (School of Economics and Management, Hebei University of Science & Technology, Shijiazhuang 050018, China)

  • Qianpeng Li

    (School of Economics and Management, Hebei University of Science & Technology, Shijiazhuang 050018, China)

  • Fachao Li

    (School of Economics and Management, Hebei University of Science & Technology, Shijiazhuang 050018, China)

  • Chenxia Jin

    (School of Economics and Management, Hebei University of Science & Technology, Shijiazhuang 050018, China)

Abstract

In order to meet customers’ demand for freshness and the time window of fresh product distribution, and achieve the sustainable development of the fresh product cold-chain logistics industry, green technology is used to solve the optimization problem of the cold-chain distribution path of a variety of fresh products, taking transportation, refrigeration, and carbon emission cost as the objective functions. A hybrid particle swarm optimization (HPSO) algorithm was designed to solve this problem with the minimum freshness requirement of different kinds of cold-chain distribution. The results show that when the minimum freshness requirement of each fresh product is 75%, the total distribution cost obtained by the hybrid particle swarm optimization algorithm is CNY 4218, and the customer satisfaction is 88.22%. While satisfying the freshness constraint, the results obtained by the particle swarm optimization algorithm reduce the total distribution cost by CNY 362 and improve customer satisfaction by 3.82%. Green technology is beneficial to reduce vehicle pollution emissions and the loss of fresh product resources, thus achieving sustainable development.

Suggested Citation

  • Lei Zhou & Qianpeng Li & Fachao Li & Chenxia Jin, 2022. "Research on Green Technology Path of Cold-Chain Distribution of Fresh Products Based on Sustainable Development Goals," Sustainability, MDPI, vol. 14(24), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16659-:d:1001468
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    References listed on IDEAS

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    1. Milita Vienažindienė & Vilma Tamulienė & Jurgita Zaleckienė, 2021. "Green Logistics Practices Seeking Development of Sustainability: Evidence from Lithuanian Transportation and Logistics Companies," Energies, MDPI, vol. 14(22), pages 1-18, November.
    2. Bing Qing Tan & Fangfang Wang & Jia Liu & Kai Kang & Federica Costa, 2020. "A Blockchain-Based Framework for Green Logistics in Supply Chains," Sustainability, MDPI, vol. 12(11), pages 1-13, June.
    3. Zhixue Zhao & Xiamiao Li & Xiancheng Zhou, 2020. "Distribution Route Optimization for Electric Vehicles in Urban Cold Chain Logistics for Fresh Products under Time-Varying Traffic Conditions," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-17, October.
    4. Su-Young Kwak & Woo-Sung Cho & Gil-Am Seok & Seung-Gyun Yoo, 2020. "Intention to Use Sustainable Green Logistics Platforms," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    5. Gaoyuan Qin & Fengming Tao & Lixia Li, 2019. "A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon Emissions," IJERPH, MDPI, vol. 16(4), pages 1-17, February.
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    Cited by:

    1. Jing Liao & Jie Tang & Andrea Vinelli & Ruhe Xie, 2024. "Sustainable fresh food cold supply chain (SFC) from a state-of-art literature review to a conceptual framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(12), pages 30817-30859, December.
    2. Baohua Zhang & Jihad Mohammad, 2024. "Sustainability of Perishable Food Cold Chain Logistics: A Systematic Literature Review," SAGE Open, , vol. 14(3), pages 21582440241, September.

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