关键词: 动态车辆路径问题, 多维数据层结构, 前摄性实时控制, 需求预测

Abstract: Based on the forecasting and solving algorithm of the uncertain demand in the dynamic vehicle routing problem with uncertain demand information in the existing literature, a multidimensional data layer customer demand forecasting method and a proactive real-time control method are established to discuss the potential customer response criteria. The mathematical model of dynamic vehicle routing problem is established by introducing proactive real-time control method with the aim of minimizing the total transportation cost. The genetic algorithm is used to solve the model. The test results show that the proposed model and algorithm can respond to the customer’s demand more timely and effectively by applying the Joybuy’s distribution data of 20 clients in Chongqing area and the two-stage comprehensive proactive adjustment strategy.

Key words: dynamic vehicle routing problem, mutli-data layer structure, pro-active real-time control method, demand forecast