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Optimizing Port Seafood Logistics Paths: A Multi-Objective Approach for Zero-Carbon and Congestion Management

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Listed:
  • Ruiqi Xiao

    (School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572024, China)

  • Min Xiao

    (Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572024, China
    School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan 430063, China)

  • Hanbin Xiao

    (School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572024, China)

  • Ze Zhu

    (School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572024, China)

Abstract

Cold chain logistics possesses unique characteristics, particularly the necessity to maintain low temperatures within containers throughout the distribution process. Real-world traffic conditions, such as congestion, significantly impact the efficiency of cold chain logistics and contribute to increased carbon emissions. To foster green and sustainable development in this sector, a carbon emission trading mechanism has been established, incentivizing companies to invest in energy conservation and emission reduction through economic transactions. This study introduces a multi-objective optimization model for route planning in port seafood logistics, integrating considerations of traffic congestion and zero-carbon transportation. To accurately reflect real-world traffic conditions, a time-dependent function is utilized to model traffic congestion within actual road networks. The road segments are divided, and the travel time for vehicles in each segment is computed. Additionally, the costs associated with the distribution process are analyzed, leading to the development of a multi-objective optimization model aimed at minimizing both distribution costs and zero-carbon transportation costs. The proposed model demonstrates significant economic savings and environmental advantages, providing a theoretical foundation for decision-making processes that support the green and sustainable development of port seafood logistics.

Suggested Citation

  • Ruiqi Xiao & Min Xiao & Hanbin Xiao & Ze Zhu, 2025. "Optimizing Port Seafood Logistics Paths: A Multi-Objective Approach for Zero-Carbon and Congestion Management," Sustainability, MDPI, vol. 17(5), pages 1-28, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:2311-:d:1606864
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    References listed on IDEAS

    as
    1. Marco Gonçalves & Cátia Salgado & Amaro de Sousa & Leonor Teixeira, 2025. "Data Storytelling and Decision-Making in Seaport Operations: A New Approach Based on Business Intelligence," Sustainability, MDPI, vol. 17(1), pages 1-26, January.
    2. Kateryna Nekit & Denis Kolodin & Valentyn Fedorov, 2020. "Personal data protection and liability for damage in the field of the internet of things," Juridical Tribune - Review of Comparative and International Law, Bucharest Academy of Economic Studies, vol. 10(1), pages 80-93, March.
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