摘要
动态供应链绩效评价是一个包含多个指标输入输出的复杂评估系统,各绩效指标具有模糊性、不确定性,绩效指标数量较多,彼此之间存在非线性关联性。针对这样一个复杂的评估系统,本文讨论利用神经网络技术来对动态供应链绩效进行综合评价。本文首先介绍了人工神经网络的基本概念。针对供应链绩效的五维平衡计分卡模型,利用BP神经网络(Back Propagation NeuralNetwork,BP网络)来对供应链综合绩效评价结果进行学习和预测,文中我们详细讨论了供应链绩效评价中BP网络的学习过程和存在的问题,并给出了仿真结果。计算实例表明本文提出的动态供应链绩效评价模型是合理、有效的,能够为供应链的合理分析和决策制定提供依据。
For the sake of integrative performance measurement of agile virtual enterprise, the traditional Balanced Scorecard is extended into 5 dimensions. According to it, incorporated with the Back Propagation Neural Network approach we could get evaluation model. A calculation example of performance measurement is provided, which shows that the suggested evaluation method is feasible and efficient for dynamic performance measurement and forecasts. Thus, it supplies reasonable analysis and policy making tools for supply chain management.
出处
《运筹与管理》
CSCD
北大核心
2010年第2期26-32,共7页
Operations Research and Management Science
关键词
供应链管理
绩效评价
动态平衡计分卡
BP神经网络
supply chain management, performance measurement, dynamic balanced scorecard, back propagation neural network.
