关键词: 动态度, 需求不确定, 两级车辆路径, 并行算法, 模拟退火算法

Abstract: Considering the dynamic characteristics of manufacturing unit needs,the line-limiting policy of large trucks and the exact constraint of delivery time,a two-echelon vehicle routing optimization method with time window considering dynamic degree was designed.Based on the customer dynamic incremental probability threshold and dynamic degree,an optimized routing update strategy in response to incremental demand was constructed.The continuous dual network optimization was innovatively mapped to the Vehicle Routing Problem with Time Windows (VRPTW) optimization of two sub-networks,including from the suburban delivery centre to the city delivery centre and from the city delivery centre to the customer.The four neighborhood search strategies of Or-opt,2-opt,2-opt* and Swap/shift were merged to improve the parallel simulated annealing algorithm.Company case was used to verify the model and method,and the results show that the proposed method could better meet the agility response of suppliers to the dynamic needs of customers,and had good robustness.

Key words: dynamic degree, uncertain demand, two-echelon vehicle routing, parallel algorithm, simulated annealing algorithm