基于时空相似测度的冷链物流分区配送路径优化

Route optimization of partitioned distribution of cold chain logistics based on spatiotemporal similarity measure

为提高生鲜品冷链物流配送的时效性,进而提高冷链配送企业的服务质量和市场竞争力,考虑客户地理位置的相邻性和交货时间窗的相似性,提出基于时空相似测度的冷链物流分区配送路径优化模型。借助基于时空相似测度的k-means聚类方法和遗传算法,实现客户的动态分区和路径优化。通过算例发现:基于时空相似测度进行分区的路径优化方案不仅在配送成本、时间惩罚成本和货损成本上明显优于基于传统的固定分区和基于空间相似测度进行分区的路径优化方案,而且时效性也明显改善。

In order to improve the timeliness of the cold chain logistics distribution of fresh products,and improve the service quality and market competitiveness of cold chain distribution enterprises,combining the adjacency of customer locations and the similarity of delivery time windows,a route optimization model for partitioned distribution of cold chain logistics is proposed based on the spatiotemporal similarity measure.By the k-means clustering method based on the spatiotemporal similarity measure and the genetic algorithm,the dynamic partitioning of customers and the route optimization are implemented.Through an example,it is evidenced that the solution of route optimization of partitioned distribution based on the spatiotemporal similarity measure outperforms those based on the traditional fixed partition and the partitioning based on the spatial measure of similarity,not only in the distribution cost,time penalty cost and cargo damage cost,but also in timeliness.