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基于熵权法的供应链物流配送风险评估算法 被引量:1

Risk Assessment Algorithm of Logistics Distribution of Supply Chain Based on Entropy Weight
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摘要 考虑到传统风险评估算法在评估供应链物流配送风险时,存在报警数量大、误报率高的问题,为此提出了基于熵权法的供应链物流配送风险评估算法。利用物流配送风险等级结合评价标准构建评估矩阵,采用熵权法对评估的物流配送风险求取风险向量,获得产生风险的主要影响因素,对物流配送风险进行归一化处理,得到供应链物流配送风险的权值,对权值的风险评估判定,计算供应链物流配送风险评估的综合权值,通过定义供应链物流配送风险的估计值,规划了供应链物流配送路径,利用熵权法,描述了供应链物流配送风险的评估指标,通过计算供应链物流配送风险的威胁度指数,得到供应链物流配送的风险评估权值,结合供应链物流配送风险评估算法设计,实现了供应链物流配送风险的评估。实验结果表明,基于熵权法的供应链物流配送风险评估算法不仅具有更高的性能,还可以保证供应链物流配送风险评估的实时性。 Considering many problems that exist in traditional way of risk assessment of logistic distribution in supply chain,such as great number of alarms with high rate of false alarms,this paper proposes a new algorithm of risk assessment based on entropy weight.The evaluation matrix is constructed by combining the risk level of logistics distribution with the evaluation standard. The risk vector is obtained with entropy weight method so that the main factors incurring risks are found out in logistic distribution.The risks are normalized and the risk weight values are obtained. Then,with the risk assessment weight,the comprehensive weight of the risk assessment of logistics distribution is calculated. By defining the estimated value of the logistics distribution risk,the distribution path of supply chain is planned.The evaluation index of logistics distribution risk is described by entropy weight method.The risk assessment weight of logistics distribution is obtained by calculating the threat index of the risks.Thus the risks of logistics distribution are assessed by designing the risk assessment algorithm of logistics distribution. The experimental results show that the entropy weight method can not only improve the performance of the risk assessment,but also ensure its instantaneity.
作者 林奎星 LIN Kui-xing(Jimei University,Xiamen,Fujian 361021,China)
出处 《武汉商学院学报》 2021年第5期51-55,共5页 Journal of Wuhan Business University
基金 厦门市物流与供应链学会委托项目《厦门市快消品供应链研究》(项目编号:H2018064)。
关键词 熵权法 供应链 物流配送 风险评估 综合权值 报警数量 entropy weight method supply chain logistics distribution risk assessment comprehensive weight the number of alarms
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