Multi-location Selection Method for Cainiao Stations Based on FCM-PSO-FWA Algorithm
With the popularization of e-commerce and the rapid growth of consumer demand for express delivery services,the location allocation of the Cainiao station,the facility for a new mode of express delivery service,is crucial to improving the efficiency and user experience of express delivery services.Most current studies focus on the location allocation of logistics distribution centers and,of the relatively small body of re-searches on the location allocation of the Cainiao station,the majority consider the location allocation of a single logistics distribution center,despite the fact that realistically,communities such as university campuses and large residential areas often need to establish multiple Cainiao stations.In this paper,we design an algorithm to solve the location allocation problem of multiple Cainiao stations in a community by integrating multiple machine learning methods,and verify the effectiveness of the pro-posed algorithm through a simulation example.First,we establish the Cainiao station location allocation model according to the parcel pickup method based on 0-1 integer programming,and use the particle swarm optimization algorithm(PSO)to find the optimal location of the Cainiao station.However,PSO can only solve the optimal location problem of a single Cainiao station through iteration,which is not viable in the case of multiple Cainiao stations.In light of this,we employ the fuzzy C-means(FCM)clustering meth-od to conglomerate all demand points according to their geographical coordinates and obtain the cluster cen-ter of each type of demand points.Then such cluster center is regarded as the initial location of the Cainiao station for each type of demand point and in this way,we divide the location allocation problem of the multi-ple Cainiao stations in a community into the location allocation problem of a single Cainiao station in multi-ple sub-communities.Next,we incorporate the Fireworks Algorithm(FWA)into the Particle Swarm Opti-mization(PSO)to deal with the locality tendency of the traditional PSO algorithm and finally apply the pro-posed FCM-PSO-FWA algorithm to the Cainiao station locatioin allocation problem with randomly gener-ated demand points of different sizes and the Cainiao station location allocation problem of Jiangnan Univer-sity.The study shows that given undefined number of demand points,the FCM-PSO-FWA algorithm can ef-fectively solve the location allocation problem of multiple Cainiao stations and will not fall into local conver-gence,thus verifying the feasibility and effectiveness of the algorithm.
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维普
