无人车辅助卡车配送路径优化研究

Research on Optimization of Delivery Path for Autonomous Vehicle Assisted Trucks

使用无人车进行物流配送具有降低配送成本、提高配送效率等优点,但无人车对周边智能交通设施和自动驾驶技术要求较高,再加上政策约束,现有L4级无人车只适合简单环境的应用。针对无人车的配送特点,本文研究具有车辆载重限制和无人车配送区域限制的无人车与有人驾驶卡车协同配送路径优化问题,建立了以耗费工作人员时间最少为目标的数学模型。设计自适应聚类领域搜索算法,首先采用k-means聚类算法结合插入操作生成初始解,其次运用自适应领域搜索算法对初始解进行改进,再使用算例证明算法的有效性,最后探讨非限制区客户比例对配送时间的影响,并证明多使用无人车可以减少配送的时间成本。

The autonomous vehicles used in logistics distribution has the advantages of reducing distribution cost and improving distribution efficiency,but autonomous vehicles have higher requirements for surrounding intelligent transportation facilities and autonomous driving technology,and the existing L4 autonomous vehicles are only suitable for the application of simple environment.According to the distribution characteristics of autonomous vehicles,the collaborative distribution route optimization problem of the vehicle routing problem with autonomous vehicles with load limit and autonomous vehicle distribution area limit was studied,and a mathematical model was established to minimize the cost of staff time.The adaptive clustering neighborhood search metaheuristic is designed.Firstly,k-means clustering algorithm combined with insertion operation is used to generate the initial solution,then the adaptive neighborhood search metaheuristic is used to improve the initial solution,and the effectiveness of the metaheuristic is demonstrated by an example.Finally,the influence of proportion of customers in non-restricted area on delivery time is discussed and it is proved that the time cost of delivery can be reduced by using more autonomous vehicles.