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Green Vehicle-Routing Problem of Fresh Agricultural Products Considering Carbon Emission

Author

Listed:
  • Qi Yao

    (Management School, Wuhan College, Wuhan 430212, China
    School of Information Management, Central China Normal University, Wuhan 430079, China)

  • Shenjun Zhu

    (School of Information Management, Central China Normal University, Wuhan 430079, China)

  • Yanhui Li

    (Management School, Wuhan College, Wuhan 430212, China
    School of Information Management, Central China Normal University, Wuhan 430079, China)

Abstract

The need to reduce carbon emission to cope with climate change has gradually become a global consensus, which also poses a great challenge to cold-chain logistics companies. It forces them to implement green distribution strategies. To help the distribution companies reduce carbon emission, this paper studies two aspects—carbon tax value and investing in the freshness-keeping cost—and proposes corresponding solutions. A new green vehicle-routing model for fresh agricultural products with the goal of minimizing the total cost is proposed. To solve the model proposed, an improved ant-colony optimization (IACO) is designed specifically. On one hand, the experimental results show that the increase in carbon tax will restrict the carbon emission behaviors of the distribution companies, but it will also reduce their economic benefits to a certain extent, at the same time. On the other hand, investing in the freshness-keeping cost can help actively achieve the carbon emission reduction target, reduce the loss of fresh agricultural products in the distribution process, improve the company’s economic benefits and satisfy customers. The comparison results of different algorithms prove that the IACO proposed in this paper is more effective in solving the model, which can help increase the economic benefits of the companies and reduce carbon emission. This study provides a new solution for cold-chain logistics distribution companies to reduce carbon emission in the distribution process, and also provides a reference for government departments to formulate carbon tax policies.

Suggested Citation

  • Qi Yao & Shenjun Zhu & Yanhui Li, 2022. "Green Vehicle-Routing Problem of Fresh Agricultural Products Considering Carbon Emission," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:14:p:8675-:d:864368
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    References listed on IDEAS

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    1. Lai, David S.W. & Caliskan Demirag, Ozgun & Leung, Janny M.Y., 2016. "A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 32-52.
    2. Devapriya, Priyantha & Ferrell, William & Geismar, Neil, 2017. "Integrated production and distribution scheduling with a perishable product," European Journal of Operational Research, Elsevier, vol. 259(3), pages 906-916.
    3. Gmira, Maha & Gendreau, Michel & Lodi, Andrea & Potvin, Jean-Yves, 2021. "Tabu search for the time-dependent vehicle routing problem with time windows on a road network," European Journal of Operational Research, Elsevier, vol. 288(1), pages 129-140.
    4. Md. Anisul Islam & Yuvraj Gajpal, 2021. "Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    5. Bogataj, David & Bogataj, Marija & Hudoklin, Domen, 2017. "Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model," International Journal of Production Economics, Elsevier, vol. 193(C), pages 51-62.
    6. Chen, Jing & Dong, Ming & Xu, Lei, 2018. "A perishable product shipment consolidation model considering freshness-keeping effort," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 56-86.
    7. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    8. Songyi Wang & Fengming Tao & Yuhe Shi & Haolin Wen, 2017. "Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax," Sustainability, MDPI, vol. 9(5), pages 1-23, April.
    9. Jin Li & Feng Wang & Yu He, 2020. "Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    10. Kitjacharoenchai, Patchara & Min, Byung-Cheol & Lee, Seokcheon, 2020. "Two echelon vehicle routing problem with drones in last mile delivery," International Journal of Production Economics, Elsevier, vol. 225(C).
    11. Songyi Wang & Fengming Tao & Yuhe Shi, 2018. "Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint," IJERPH, MDPI, vol. 15(1), pages 1-17, January.
    12. 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.
    13. Zhang, Shuai & Gajpal, Yuvraj & Appadoo, S.S. & Abdulkader, M.M.S., 2018. "Electric vehicle routing problem with recharging stations for minimizing energy consumption," International Journal of Production Economics, Elsevier, vol. 203(C), pages 404-413.
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    Cited by:

    1. Ratko Stanković & Tomislav Pereglin & Tomislav Erdelić, 2023. "Optimizing Utilization of Transport Capacities in the Cold Chain by Introducing Dynamic Allocation of Semi-Trailers," Logistics, MDPI, vol. 7(4), pages 1-22, December.

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