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The Vehicle Routing Problem with Time Windows Based on a Multi-conditional Clustering and Tabu Search Approach

In: Liss 2023

Author

Listed:
  • Yuhong Pan

    (Central University of Finance and Economics)

  • Xi Wang

    (Central University of Finance and Economics)

  • Hui Li

    (Central University of Finance and Economics)

Abstract

A company distributes goods to stores all over the country through one warehouse. The warehouse processes orders from different stores daily and decides on order allocation and shipping routes for each vehicle. In a long-haul transport, drivers must obey traffic safety regulations, such as day/night speed limits and continuous driving hours. This paper considers a long-haul vehicle routing problem in terms of time windows and order priorities. An integer programming model is built to minimize the total transportation time of all vehicles. Then, a multi-conditional clustering method based on K-means is adopted to achieve regional division. Moreover, a Tabu Search (TS) algorithm, based on the regional division with creating mixed neighborhood structure, is proposed to optimize the solutions for the model. The preliminary results of a series of experiments, which are conducted on real data, are able to verify the effectiveness and efficiency of the proposed algorithm.

Suggested Citation

  • Yuhong Pan & Xi Wang & Hui Li, 2024. "The Vehicle Routing Problem with Time Windows Based on a Multi-conditional Clustering and Tabu Search Approach," Lecture Notes in Operations Research, in: Daqing Gong & Yixuan Ma & Xiaowen Fu & Juliang Zhang & Xiaopu Shang (ed.), Liss 2023, pages 270-282, Springer.
    • Handle: RePEc:spr:lnopch:978-981-97-4045-1_21
    DOI: 10.1007/978-981-97-4045-1_21
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