Model and Algorithm of Logistics Distribution Path Optimization in B2C E-Commerce

The characteristics of scattered customer locations, many orders, small batch and many repeated routes. The traditional route optimization methods encounter various problems to varying degrees. Aiming at the distribution path optimization, in the first stage, the customer group is divided into several regions by K-means clustering method, and in each region, a scanning algorithm is used to decompose several small-scale model subsets that meet the constraints; In the second stage, the improved problem of individual TSP model for the customer points in each group. B2C e-commerce logistics distribution path optimization model and algorithm, which is a model to predict and optimize the distribution path of goods from the factory to the customer. B2C e-commerce logistics distribution path optimization model calculates the best way to optimize transportation cost, inventory consumption rate, shipment time, etc. It also calculates a set of parameters, such as the minimum distance between the factory and the warehouse, to optimize transportation costs.