摘要
为确保冷链物流在缩减成本的同时满足农产品品质需求,以异构数据为基础,提出一种农产品冷链物流节点部署方法。基于可扩展标记语言文档,利用数据源模块、转变模块、集成模块以及应用模块,构建异构数据集成模型;根据集成的物流异构数据,架构冷链物流节点部署模型,采用粒子群优化算法进行求解,获取节点方位,通过分析影响寻优性能的极大速度与加速常数等指标参数取值范围,完善农产品冷链物流节点部署结果。仿真结果表明,所提方法的设计方案的配送成本与需求量满足度最优,具有较好的有效性。
This paper presents a node deployment method for agricultural cold chain logistics based on heterogeneous data, in order to reduce the cost of cold chain logistics and meet the quality requirements of agricultural products. According to extensible markup language(XML) documents, data source module, transformation module, integration module and application module were applied to found heterogeneous data integration model. The cold chain logistics node deployment model was constructed via the integration of logistics heterogeneous data. Particle swarm optimization algorithm was used for obtaining the node orientation. The maximum speed and acceleration constant affecting the optimization performance were analyzed in detail, improving the deployment results of agricultural cold chain logistics nodes. The simulation results show that the distribution cost and demand satisfaction of the design scheme of the proposed method are the best and have good effectiveness.
作者
张慧
滕志霞
ZHANG Hui;TENG Zhi-xia(Jilin University of Architecture and Technology,School of Management Engineering,Jilin Changchun 130114,China;Northeast Forestry University,School of information and Computer Engineering,Heilongjiang Haerbin 150040,China)
出处
《计算机仿真》
北大核心
2022年第2期467-471,共5页
Computer Simulation
基金
2020年度吉林省教育厅科学研究规划项目(JJKH20201243SK)。
关键词
异构数据
农产品
冷链物流
节点部署
可扩展标记语言
粒子群优化算法
Heterogeneous data
Agricultural products
Cold chain logistics
Node deployment
extensible markup language
Particle swarm optimization algorithm
