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Optimization of Fresh Food Logistics Routes for Heterogeneous Fleets in Segmented Transshipment Mode

Author

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  • Haoqing Sun

    (School of Business Administration, Liaoning Technical University, Huludao 125105, China)

  • Manhui He

    (Bohai Shipbuilding Vocational College, Huludao 125105, China)

  • Yanbing Gai

    (School of Business Administration, Liaoning Technical University, Huludao 125105, China)

  • Jinghao Cao

    (School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China)

Abstract

To address the challenges of environmental impact and distribution efficiency in fresh food logistics, a segmented transshipment model involving the coordinated operation of gasoline and electric vehicles is proposed. The model minimizes total distribution costs by considering transportation, refrigeration, product damage, carbon emissions, and penalties for time window violations. The k-means++ clustering algorithm is used to determine transshipment points, while an improved adaptive multi-objective ant colony optimization algorithm (IAMACO) is employed to optimize the delivery routes for the heterogeneous fleet. The case study results show that compared to the traditional model, the segmented transshipment mode reduces the total distribution costs, carbon emissions, and time window penalty costs by 22.13%, 28.32%, and 41.08%, respectively, providing a viable solution for fresh food logistics companies to achieve sustainable and efficient growth.

Suggested Citation

  • Haoqing Sun & Manhui He & Yanbing Gai & Jinghao Cao, 2024. "Optimization of Fresh Food Logistics Routes for Heterogeneous Fleets in Segmented Transshipment Mode," Mathematics, MDPI, vol. 12(23), pages 1-28, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:23:p:3831-:d:1536398
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    References listed on IDEAS

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    1. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    2. Yiqin Lu & Shuang Li, 2023. "Green Transportation Model in Logistics Considering the Carbon Emissions Costs Based on Improved Grey Wolf Algorithm," Sustainability, MDPI, vol. 15(14), pages 1-15, July.
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    Cited by:

    1. Tingxin Wen & Haoting Meng, 2025. "Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy," Mathematics, MDPI, vol. 13(7), pages 1-27, March.

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