基于K-means算法和遗传算法两阶段融合模型的物流配送线路优化

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中图分类号：TP18；TP39 文献标识码：A 文章编号：2096-4706（2025）15-0168-07

Abstract： Inorder toachieve the goalofcostcontrolandeficiency enhancement in cigarette logistics distribution，this paper combines K-means algorithm with Genetic Algorithm，and constructs alogistics distribution route optimization model basedonbusinesconstraints.Basedonthenationalsalesdataof independentbrandcigarettes in2O23，according tothelatitude andlongitudeofthereceivingcityK-meansclusteringalgorithmisusedforclusteringoperation.Inorder tomettheactual business eedsandfurtherreduce thecostoflogisticsandtransportation，analgorithmtobalance thenumberofcitiesandtonkilometers isdesignedtore-optimizetheclusteringresults.Finaly，GeneticAlgorithmisusedtosolvetheshortestpath for clusteringresults.Theexample analysis shows thatthecalculationresultsof themodel are basicallyconsistent withthe actual line.Compared withthe traditionalmanualrouteplaning method，thecumbersomeprocessissimplifedandthe trasportation eficiencyisimproved.The modelcanprovideapowerfulreferencefortransportationroute planning，andcanquicklyplan transportation routes to help achieve cost control and effciency improvement ofcigarete logistics distribution.

Keywords： K-means algorithm; balancing ton-kilometer; Genetic Algorithm; distribution route optimization; cost control and efficiency enhancement

0 引言

近些年随着卷烟工商交易逐步实行“按订单组织货源”模式，市场需求分散，小批量、多频次订单逐渐成为新常态，导致物流成本不断增加。（剩余8563字）