摘要
文中基于生鲜农产品冷链运输的发展现状,发现路况和冷链管理对冷链运输效率有显著影响,于是利用Lasso回归分析对路况和冷链管理中的主要影响因素进行筛选和验证,将不确定因素通过量化的方式考虑在最优路径的规划中建立优化模型,提高Floyd算法的兼容性,并建议企业重视动态路况因素并利用改进Floyd算法优化配送站点布局,进一步缩短延误时间,节省冷链成本。
Based on the development status of cold chain transportation of fresh agricultural products, this paper finds that road conditions and cold chain management have a significant impact on the efficiency of cold chain transportation, then uses Lasso regression analysis to screen and verify the main influencing factors in road conditions and cold chain management, and considers the uncertain factors in the planning of the optimal path through quantitative methods to establish an optimization model for improving the compatibility of Floyd algorithm.It is also suggested that enterprises should pay attention to the dynamic road conditions and optimize the distribution station layout by using the improved Floyd algorithm to further shorten the delay time and save the cold chain cost.
作者
袁梦婷
张雨洁
YUAN Meng-ting;ZHANG Yu-jie(School of Economics and Management,Nanjing Forestry University,Nanjing 210037,China)
出处
《物流工程与管理》
2023年第2期50-52,49,共4页
Logistics Engineering and Management
基金
南京林业大学2022年大学生创新创业训练计划项目“‘双循环’视角下绿色物流与经济高质量发展的协调关系研究”(202110298022Z),指导教师:廖吉林。
关键词
生鲜农产品
冷链物流
路径优化
Lasso回归
FLOYD算法
fresh agricultural products
cold chain logistics
path optimization
Lasso regression analysis
Floyd algorithm
