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Feasibility on the integration of passenger and freight transportation in rural areas: A service mode and an optimization model

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  • Yang, Tiannuo
  • Chu, Zhongzhu
  • Wang, Bailin

Abstract

Public transport operators in rural areas have been under pressure from weak profitability and emission issues. At the same time, scattered demand for transport has been preventing logistics systems from reaching the last mile in residential areas. Multimodal transport can synergistically integrate passenger and freight demand, increase transportation network coverage, and reduce the cost of transportation, while demand-driven services improve the flexibility and reliability of operational decisions. Therefore, this paper proposes a demand-driven passenger-and-freight-integration service (DDPFIS) mode. From the perspective of routing decisions, a new mixed-integer linear programming model based on the green vehicle routing problem is formulated to assist public transport operator’s complex decision-making. In the proposed model, vehicle capacity is fully utilized through a combination of passenger and freight demand so that optimal decisions are made about vehicle routing. Numerical experiments are designed and conducted based on realistic instances with the results indicating that: the DDPFIS mode enables effective integration of different demands, leading to high-level vehicle capacity utilization and cost reduction; and compared with two conventional models of vehicle routing problems, the proposed model achieves lower fuel consumption and cost for all problem sizes. In addition, some important management insights are provided, e.g., a greater proportion of integrated service nodes is not necessarily better; and it is more suitable to provide a service for rural residents who are relatively insensitive to time.

Suggested Citation

  • Yang, Tiannuo & Chu, Zhongzhu & Wang, Bailin, 2023. "Feasibility on the integration of passenger and freight transportation in rural areas: A service mode and an optimization model," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:soceps:v:88:y:2023:i:c:s0038012123001775
    DOI: 10.1016/j.seps.2023.101665
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