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Low Carbon Logistics Location Problem Under Multi-Vehicle Route

In: Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)

Author

Listed:
  • Kaiwei Jia

    (Liaoning Technical University)

  • Jue Wang

    (Liaoning Technical University)

Abstract

In order to solve the decision-making problem of distribution center location and multi-vehicle routing optimization combination under the background of low carbon emission, a planning model aiming at the minimum logistics comprehensive cost considering carbon emission was proposed, and a two-stage heuristic algorithm was designed to solve the problem. In the first stage, the improved k-means clustering method is designed to partition and cluster the customer nodes, and then the spatial single journey partitioning algorithm is used to determine the customers served by each distribution center with the full load condition as the limit. In the second stage, the lowest comprehensive logistics cost is taken as the optimization objective, and the quantum genetic algorithm is established to solve the problem. Combined with the data of a logistics company, it is shown that compared with other existing algorithms, the algorithm proposed in this paper can effectively reduce the comprehensive cost of logistics under the premise of low carbon emissions, and provides a new way to solve the problem of site-multi-vehicle routing.

Suggested Citation

  • Kaiwei Jia & Jue Wang, 2024. "Low Carbon Logistics Location Problem Under Multi-Vehicle Route," Advances in Economics, Business and Management Research, in: Suhaiza Hanim Binti Dato Mohamad Zailani & Kosga Yagapparaj & Norhayati Zakuan (ed.), Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), pages 1501-1515, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-256-9_152
    DOI: 10.2991/978-94-6463-256-9_152
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