中文摘要：

为了提高车辆配送初始解获得的效率，在不确定条件下，研究了上海世博会行李跟随系统需求点的空间特性，提出了基于空间特性的车辆调度方法，建立了需求点的空间特性SLINK聚类分析方法和聚类分析结果评估方法。计算结果表明：在需求点群聚状态下，采用基于空间特性的聚类分析法的调度初始解总距离为583，而传统SWEEP扫描法的调度初始解总距离为595，因此，在对车辆调度问题进行求解时，对需求点的空间分布特性进行分析有助于不确定环境下车辆调度问题的最终求解。

英文摘要：

In order to improve the efficiency of initial solution for vehicle routing problem（VRP）, the spatial characters of demand points for hands-free travel system in Shanghai World Expo were studied under uncertainly conditions. Vehicle routing method was put forward based on the spatial characters, and the Single-LINkage（SLINK） clustering method for the spatial characters and the estimation method for the clustering analysis result were built. Computation result indicates that the Single-LINkage clustering method can get the total distance of 583 for the initial solution, and the SWEEP method gets 595 when the demand points are clustering, so the analysis of spatial character for demand points contributes to the last solving for the VRP under the uncertainly conditions. 3 tabs, 5 figs, 8 refs