运用AP聚类算法分析冷链配送中心选址对物流成本的影响

IF 4 Q2 ENGINEERING, INDUSTRIAL
Kun He
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引用次数: 1

摘要

摘要配送中心是物流网络中货物的中转场所,用来实现货物的配送。与普通物流相比,冷链物流由于运输对象的低温或超低温要求,对时效性有更高的要求。针对冷链配送中心选址成本高、效率低的问题,提出了一种新的冷链配送中心选址模型。采用亲和性传播(Affinity Propagation, AP)聚类算法简化位置选择。并将二值语义与熵相结合,降低了二值语义在实验过程中的主观性。结果表明,采用该方法进行的选址是最优的,不会出现多个二级配送中心为同一零售商的问题。该研究方法对于冷链配送中心选址更加客观、科学。与普通物流相比,冷链物流对及时性的要求更高。配送中心是物流网络中货物的中转场所,在物流供应链系统中起着重要的作用。提出了一种新的冷链配送中心选址模型。采用亲和传播(Affinity Propagation, AP)聚类算法简化位置选择,并将二值语义与熵值法相结合,可以进一步提高影响因素指标权重的客观性。结果表明,研究方法不会出现多个二级配送中心为同一零售商提供物流服务的问题,区位选择结果是最优的。物流成本可降低0.042%。本研究提高了配送效率,增强了冷链物流配送的客户体验,为冷链物流配送的发展提供了一定的技术和参考价值。关键词:AP聚类算法成本配送中心冷链物流选址披露声明作者未报告潜在利益冲突。贺坤(音译),滁州职业技术学院经济学专业教师。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AP clustering algorithm for analysis of the impact of cold chain distribution center location on logistics costs
ABSTRACTThe distribution center is a transit place for goods in the logistics network, used to achieve the distribution of goods. Compared with ordinary logistics, cold chain logistics has higher requirements for timeliness due to the low temperature or ultra-low temperature requirements of transport objects. Aiming at the problems of high cost and low efficiency of cold chain distribution center location, a new location model of cold chain distribution center is developed. The Affinity Propagation (AP) clustering algorithm is used to simplify location selection. And combine the binary semantics with entropy to reduce the subjectivity of the binary semantics in the process of experiment. The results show that the location selection using the research method is optimal, and the problem that multiple secondary distribution centers are the same retailer will not appear. The research method is more objective and scientific for the location of cold chain distribution centers.Compared with ordinary logistics, cold chain logistics has higher requirements for timeliness. Distribution center is the transfer place of goods in the logistics network, which plays an important role in the logistics supply chain system. A new location model of cold chain distribution center is developed. Using Affinity Propagation (AP) clustering algorithm to simplify location selection and combining binary semantics with entropy method can further improve the objectivity of influencing factor index weights. The results show that the problem of multiple secondary distribution centers providing logistics services for the same retailer will not occur in the research method, and the location selection results are optimal. And the logistics cost can be reduced by 0.042%. This study improves the distribution efficiency, enhances the customer experience of cold chain logistics distribution, and provides certain technology and reference value for the development of cold chain logistics distribution.KEYWORDS: AP clustering algorithmcostdistribution centercold chain logisticssite selection Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsKun HeKun He, a teacher at Chuzhou Polytechnic, specializing in the field of economics.
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
21
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