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Platform-based stable truck matching problem with trailer-swapping mode

Author

Listed:
  • Peng, Wenxiang
  • Chen, Xiangsheng
  • Xue, Zhaojie
  • Liao, Yubin
  • You, Jintao

Abstract

This study investigates the platform-based stable truck-matching problem with trailer-swapping mode (STMP-TSM). The TSM is a novel collaborative transportation approach in which trucks participate in trailer swapping, significantly decreasing the rate of empty trucks and reducing transportation costs. In the STMP-TSM, a platform delivers a trailer-swapping scheme that satisfies all participating trucks. Correspondingly, an integer linear programming model is developed to maximize the total truck utility of the STMP-TSM. A specific preference list based on a chain-data structure is meticulously constructed to obtain a stable matching scheme. The preference list enables more generalized truck matching. In addition, a series of acceleration strategies is proposed to expedite the generation of a preference list while effectively reducing its length. An iterative preference-list-trim heuristic algorithm is designed, which strategically trims chains in the preference list to solve the STMP-TSM efficiently. As a benchmark, an integer linear programming model is developed based on the preference list to solve the truck-matching problem using the TSM. Finally, a series of numerical experiments are conducted to evaluate the performance of the proposed algorithm, assess the practicality of the TSM, and analyze the influences of the key parameters.

Suggested Citation

  • Peng, Wenxiang & Chen, Xiangsheng & Xue, Zhaojie & Liao, Yubin & You, Jintao, 2024. "Platform-based stable truck matching problem with trailer-swapping mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:transe:v:188:y:2024:i:c:s1366554524002291
    DOI: 10.1016/j.tre.2024.103638
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