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Optimization of multipath cold-chain logistics network

  • Soft computing in decision making and in modeling in economics
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Abstract

Cold-chain logistics presents significant challenges to sustainable development in terms of economics, society, and the environment. To address this issue, this paper focuses on solving a real-world problem—the multipath location-routing problem-based cold-chain logistics (MPLRPCCL), which considers soft time windows and heterogeneous fleets. The mathematical model aims to optimize the total logistics costs, including fuel consumption, carbon emissions, cargo deterioration, penalties, operating depots, and renting fleets. To effectively solve this problem, the paper proposes three versions of a memetic algorithm (MA) that incorporate control modules for monitoring the MA’s performance and improving its global optimization performance. Computational evaluations were conducted, and the results show that the proposed algorithms are effective and outperform the classic MA framework. Furthermore, the proposed model and algorithms were applied to real-world cases in Hangzhou city, China, demonstrating their practical applicability. Overall, this paper offers a promising approach to tackling the complex challenges posed by cold-chain logistics and contributes to the sustainable development of this important field.

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Funding

This work is supported by the Fundamental Research Funds for the Provincial Universities of Zhejiang GK239909299001-019, and the Research Foundation of Hangzhou Dianzi University (KYS335622091; KYH333122029M. The authors acknowledge the Supercomputing Center of Hangzhou Dianzi University for providing computing.

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Authors and Affiliations

  1. Department of Digital Media Technology, Hangzhou Dianzi University, Hangzhou, 310018, China

    Guodao Zhang, Liting Dai & Xuesong Yin

  2. The Key Laboratory of Computer Vision and Systems (Ministry of Education), Tianjin University of Technology, Tianjin, 300384, China

    Guodao Zhang

  3. College of Engineering, Ocean University of China, Qingdao, 266100, China

    Guodao Zhang

  4. Department of Mechanical Engineering, Hangzhou City University, Hangzhou, 310015, China

    Longlong Leng

  5. College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China

    Huiling Chen

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  1. Guodao Zhang
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  2. Liting Dai
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  3. Xuesong Yin
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  4. Longlong Leng
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  5. Huiling Chen
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Correspondence to Xuesong Yin or Longlong Leng.

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Zhang, G., Dai, L., Yin, X. et al. Optimization of multipath cold-chain logistics network. Soft Comput 27, 18041–18059 (2023). https://doi.org/10.1007/s00500-023-09013-y

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