Research On Location Routing Optimization Of A Fresh E-commerce Community Distribution Center

Urban inhabitants in China’s consumption levels have seen a rise,leading to a burgeoning demand for high-quality and varied consumption from urban consumers.This has opened up a wide market for e-commerce platforms,and the enhancement of cold chain logistics infrastructure further enhances the service quality of new e-commerce platforms.Despite the fact that cold chain delivery still faces issues,such as inadequate cold chain systems,extended transportation times,and perishable fresh products during transport,these issues have a direct bearing on the profitability and customer contentment of fresh e-commerce.Due to the high residential density of urban communities,more and more fresh e-commerce platforms are focusing on serving customers within urban communities.Therefore,by selecting the location of community distribution centers and optimizing the service path of delivery vehicles,these two major means play an important role in improving customer satisfaction,ensuring product freshness,and avoiding high management costs for e-commerce platforms.An example of A Fresh E-commerce’s community delivery business in Chang’an District,Xi’an City is taken for this article,which examines the current distribution situation from three perspectives:community delivery scenarios,models,and processes of delivery.It summarizes the existing problems of A Fresh E-commerce’s delivery business,including high delivery model costs,high fresh product damage rates,and unreasonable distribution vehicle scheduling arrangements.In order to solve the current delivery difficulties faced by A fresh e-commerce,this article proposes to adopt the "front-end warehouse+community distribution center" model,and considering the reality and particularity of urban road network delivery scenarios,crawling the geographic coordinates and vehicle navigation data of the target area community from the Amap developer platform to form a modeling basis.This article constructs a location and path optimization model with the goal of minimizing comprehensive costs.A simulated annealing algorithm and genetic algorithm were designed on MATLAB R2016.Through three stages of customer clustering,hierarchical location selection,and path optimization,the A fresh e-commerce community distribution center location optimization example in Chang’an District,Xi’an City was solved.The relative optimal solution was obtained under the minimum comprehensive cost objectives of distribution management costs,fresh product damage,and time window penalties.The results of the comparison analysis show that the cost of the front warehouse+community distribution center" model is reduced by more than 30%under the same logistics and distribution environment.In this paper,we construct two types of optimization models and design optimization algorithms to solve them,which not only improve the logistics and distribution efficiency of fresh produce merchant A,provide decision support for managers to plan the distribution plan,and enhance the market competitiveness of fresh produce merchant A in the urban area,but also provide a reference for the research of multiple distribution centers and path optimization in the urban area community distribution scenario.It also provides a reference for the study of multiple distribution centers and route optimization in urban community distribution scenarios.