基于深度学习的农产品物流配送中心选址决策优化研究  

Optimization study on site selection decision of agricultural logistics distribution center based on deep learning

作　　者：武士文 奚雷[1] Wu Shiwen;Xi Lei(Anhui Science and Technology University,Bengbu,Anhui,233000)

机构地区：[1]安徽科技学院,安徽蚌埠233000

出　　处：《市场周刊》2024年第13期9-13,共5页Market Weekly

基　　金：安徽省高校科学研究项目重点项目“绿色税收驱动制造业绿色转型:路径选择与激励机制”(项目编号:2023AH051829);安徽科技学院人才项目(项目编号:GLYJ202105);安徽科技学院校级重点项目(项目编号:xj2022168)。

摘　　要：为了提高城市农产品物流配送效率,降低农产品配送成本,需要规划建设城市农产品物流配送中心,文章提出了一种考虑成本与配送时间的配送中心选址优化模型方法,根据不同小区位置及需求数量,采用K-Means算法预测农产品配送中心的位置,并确定小区需求点所归属的配送中心,旨在最大限度地减少配送成本和时间,以提高城市农产品物资配送效率。最后通过案例数值仿真表明该模型能够有效地确定复杂的城市农产品物流配送中心位置,对降低配送中心选址成本至关重要。In order to improve the efficiency of urban agricultural products logistics and distribution and reduce the cost of agricultural products distribution,it is necessary to plan and build urban agricultural products logistics and distribution centers,this paper puts forward a distribution center site selection optimization model method considering the cost and distribution time,according to the location of differ-ent districts and the number of demand,the K-Means algorithm is used to predict the location of agricultural material distribution centers,and to determine the distribution center to which the district demand points belong center,aiming to minimize the distribution cost and time,in order to improve the efficiency of urban agricultural material distribution.Finally,numerical simulation shows that the model can ef-fectively determine the location of complex urban agricultural logistics distribution centers,which is crucial for reducing the cost of distribu-tion center location.

关 键 词：农产品 物流配送 深度学习 选址决策 

分 类 号：F326.6[经济管理—产业经济] TP18[自动化与计算机技术—控制理论与控制工程]