关键词: 综合运输, 车机联合, 聚类算法, 限制区物流, 路径研究

Abstract: Considering that there are restricted areas in disaster areas, epidemic areas, etc., as well as long time and is low efficiency in logistics distribution, logistics companies try to combine the characteristics of trucks and drones to maximize strengths and avoid weaknesses, and “truck+drone”, delivery mode is adopted for delivery. This paper proposes a solution for the delivery of UAVs supported by a truck carrying multiple UAVs for the next vehicle in the restricted area, and constructs a two-layer solving method with the minimum service time as the optimization goal. The first layer, a multi-stage fusion clustering algorithm that combining the different characteristics of DBSCAN clustering and [K]-means clustering for the selection of truck stops is designed. The second layer, based on the vehicle routing problem, is designed and constructed using the ant colony-simulated annealing fusion algorithm. One vehicle carries a distribution route in the form of multiple UAVs. Through solving different examples, the computational performance of the algorithm and the superiority of fusion clustering are verified. Taking a county logistics distribution as an example, the results show that it is an effective solution. In the case of regional restrictions, the final service time is also shortened by 41.4% compared with the traditional distribution mode, which effectively improves the efficiency of terminal logistics distribution.

Key words: integrated transportation, vehicle-drone combination, clustering algorithm, restricted area logistics, path research