The Optimization of Split Demand Route Planning Under Metro-Truck Collaborative Distribution

Abstract

With the evolution of people's consumption habits and the rapid growth of urban logistics, the number of trucks and delivery frequency has increased significantly, exacerbating urban traffic congestion and environmental pollution. Consequently, there is an urgent need to improve the current inefficient and highly polluted distribution mode. Currently, in most cities in China, the metro passenger flow is insufficient, and the capacity is excessive during off-peak hours, resulting in underutilized carriage capacity. The integration of surface and underground transport resources can effectively address these issues and facilitate complementary advantages and win–win cooperation between express companies and metro enterprises. This study proposes an innovative problem of split demand route planning in the cooperative distribution system involving express companies and subways. A cooperative distribution model is developed to minimize the total cost, and solved by the Cuckoo Search algorithm to obtain the optimized solution. The model is applied to the urban rail transit network in Changchun, and the results demonstrate that it is effective in reducing truck mileage and distribution costs. Compared to the single delivery pattern by trucks, the cooperative distribution approach proves to be more cost-effective and environmentally friendly.

Keywords

Subway logistics / Collaborative distribution / Split demand / Cuckoo Search algorithm / Route planning

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Funding

Innovative Research Group Project of the National Natural Science Foundation of China(71871103)

Scientific Research Project of Jilin Education Department(JJKH20231189KJ)