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A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon Emissions

Author

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  • Gaoyuan Qin

    (College of Mechanical Engineering, Chongqing University, Chongqing 400044, China)

  • Fengming Tao

    (College of Mechanical Engineering, Chongqing University, Chongqing 400044, China)

  • Lixia Li

    (College of Mechanical Engineering, Chongqing University, Chongqing 400044, China)

Abstract

Under fierce market competition and the demand for low-carbon economy, cold chain logistics companies have to pay attention to customer satisfaction and carbon emissions for better development. In order to simultaneously consider cost, customer satisfaction, and carbon emissions in the cold chain logistics path optimization problem, based on the idea of cost–benefit, this paper proposes a comprehensive cold chain vehicle routing problem optimization model with the objective function of minimizing the cost of unit satisfied customer. For customer satisfaction, this paper uses the punctuality of delivery as the evaluation standard. For carbon emissions, this paper introduces the carbon trading mechanism to calculate carbon emissions costs. An actual case data is used with a cycle evolutionary genetic algorithm to carry out computational experiments in the model. First, the effectiveness of the algorithm and model were verified by a numerical comparison experiment. The optimization results of the model show that increasing the total cost by a small amount can greatly improve average customer satisfaction, thereby obtaining a highly cost-effective solution. Second, the impact of carbon price on total costs, carbon emissions, and average customer satisfaction have also been numerically analyzed. The experimental results show that as carbon price increases, there are two opposite trends in total costs, depending on whether carbon quota is sufficient. Increasing carbon price within a certain range can effectively reduce carbon emissions, but at the same time it will reduce average customer satisfaction to a certain extent; there is a trade-off between carbon emissions and customer satisfaction. This model enriches the optimization research of cold chain logistics distribution, and the study results complement the impact research of carbon price on carbon emissions and customer satisfaction. Finally, some practical managerial implications for enterprises and government are offered.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:4:p:576-:d:206511
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    References listed on IDEAS

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    Cited by:

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    3. Wenzhu Liao & Lin Liu & Jiazhuo Fu, 2019. "A Comparative Study on the Routing Problem of Electric and Fuel Vehicles Considering Carbon Trading," IJERPH, MDPI, vol. 16(17), pages 1-25, August.
    4. Qiang Fu & Yurou Sun & Lei Wang, 2022. "Risk Assessment of Import Cold Chain Logistics Based on Entropy Weight Matter Element Extension Model: A Case Study of Shanghai, China," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    5. Hailin Wu & Fengming Tao & Qingqing Qiao & Mengjun Zhang, 2020. "A Chance-Constrained Vehicle Routing Problem for Wet Waste Collection and Transportation Considering Carbon Emissions," IJERPH, MDPI, vol. 17(2), pages 1-21, January.
    6. Longlong Leng & Yanwei Zhao & Jingling Zhang & Chunmiao Zhang, 2019. "An Effective Approach for the Multiobjective Regional Low-Carbon Location-Routing Problem," IJERPH, MDPI, vol. 16(11), pages 1-28, June.
    7. Ao Lv & Baofeng Sun, 2022. "Multi-Objective Robust Optimization for the Sustainable Location-Inventory-Routing Problem of Auto Parts Supply Logistics," Mathematics, MDPI, vol. 10(16), pages 1-22, August.
    8. Benyamin Moghaddasi & Amir Salar Ghafari Majid & Zahra Mohammadnazari & Amir Aghsami & Masoud Rabbani, 2023. "A green routing-location problem in a cold chain logistics network design within the Balanced Score Card pillars in fuzzy environment," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-33, July.
    9. Hailin Wu & Fengming Tao & Bo Yang, 2020. "Optimization of Vehicle Routing for Waste Collection and Transportation," IJERPH, MDPI, vol. 17(14), pages 1-26, July.
    10. Bin Xu & Jie Sun & Zhiming Zhang & Rui Gu, 2023. "Research on Cold Chain Logistics Transportation Scheme under Complex Conditional Constraints," Sustainability, MDPI, vol. 15(10), pages 1-28, May.
    11. Changlu Zhang & Liqian Tang & Jian Zhang & Liming Gou, 2023. "Optimizing Distribution Routes for Chain Supermarket Considering Carbon Emission Cost," Mathematics, MDPI, vol. 11(12), pages 1-20, June.
    12. Lihua Liu & Aneng He & Tian Tian & Lai Soon Lee & Hsin-Vonn Seow, 2024. "Bi-Objective Mixed Integer Nonlinear Programming Model for Low Carbon Location-Inventory-Routing Problem with Time Windows and Customer Satisfaction," Mathematics, MDPI, vol. 12(15), pages 1-35, July.
    13. Lin Lu & Song Hu & Yuelin Ren & Kai Kang & Beibei Li, 2022. "Research on Extension Design of Emergency Cold Chain Logistics from the Perspective of Carbon Constraints," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    14. Ling Shen & Fengming Tao & Yuhe Shi & Ruiru Qin, 2019. "Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions," IJERPH, MDPI, vol. 16(16), pages 1-18, August.
    15. 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.
    16. Hang Thi Thanh Vu & Jeonghan Ko, 2023. "Inventory Transshipment Considering Greenhouse Gas Emissions for Sustainable Cross-Filling in Cold Supply Chains," Sustainability, MDPI, vol. 15(9), pages 1-22, April.

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