摘要
针对常规供应链风险动态识别方法导致识别正确率较低的问题,提出基于工业互联网和蚁群优化算法的供应链风险动态识别方法。根据供应链风险管理流程,利用工业互联网技术识别供应链风险因素,在风险因素基础上构建供应链风险指标体系;通过分析风险因子的根本特征,分析潜在风险因素,并利用蚁群优化算法计算各风险指标的权重值与损失函数,结合信息素模长,实现供应链风险动态识别。对比实验结果表明:将该方法应用于企业物资供应链风险动态识别中,可取得较高的识别正确率。
Aiming at the problem that the conventional dynamic identification method of supply chain risk leads to low identification accuracy,a dynamic identification method of supply chain risk based on industrial internet and ant colony optimization algorithm is proposed.According to the supply chain risk management process,the industrial internet technology is used to identify the supply chain risk factors,and the supply chain risk index system is constructed on the basis of the risk factors.By analyzing the fundamental characteristics of the risk factors,the potential risk factors are analyzed,and the ant colony optimization algorithm is used to calculate the weight value and loss function of each risk index,combined with the pheromone modulus,the dynamic identification of supply chain risk is realized.The comparative experimental results show that the method can achieve higher recognition accuracy when applied to the dynamic risk identification of enterprise material supply chain.
作者
程栋
张勇
邱琼
Cheng Dong;Zhang Yong;Qiu Qiong(Shaoxing Power Supply Company,State Grid Zhejiang Electric Power Co.,Ltd.,Shaoxing 312000,China)
出处
《兵工自动化》
北大核心
2025年第8期68-72,共5页
Ordnance Industry Automation
关键词
工业互联网
蚁群优化算法
供应链
风险动态识别
industrial internet
ant colony optimization algorithm
supply chain
dynamic risk identification
