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订货型生产企业中生产优先权的确定是制订生产排程的关键问题.约束理论、线性规划理论、战略理论、层次分析法以及熵权法等均从不同角度给出了订单优先权决策的理论和方法.针对订单优先权确定中的现有理论和方法的不足,构建了更为系统和完善的供应链环境下的订单优先权评价指标体系,在此基础上提出了基于RBF神经网络的供应链环境下确定订单优先权的新方法,并在实证研究中对比分析了三种不同决策方法下的评价效果.研究结果表明:供应链环境下基于RBF神经网络的订单优先权评价方法明显地优于基于BP神经网络的评价方法,更优于传统的基于层次分析法的评价方法,具有评价结果准确和训练时间短等优点.
The determination of the production priority in the order-type manufacturing enterprise is the key issue in the production scheduling.Constrained theory, linear programming theory, strategic theory, analytic hierarchy process and entropy method give the theory of order priority decision-making from different angles And methods.Aiming at the shortage of the existing theories and methods in the determination of order priority, a more systematic and complete evaluation index system of order priority under the supply chain environment is established. On the basis of this, a supply system based on RBF neural network Chain environment to determine the order priority, and in the empirical study comparative analysis of three different decision-making under the evaluation of the results show that: supply chain environment based on RBF neural network order priority evaluation method significantly superior The evaluation method based on BP neural network is better than the traditional evaluation method based on AHP, which has the advantages of accurate evaluation results and short training time.