基于GA-BP神经网络的船用柴油机制造企业供应商评价

Supplier Evaluation of Marine Diesel Engine Manufacturers Based on GA-BP Neural Network

根据船用柴油机制造企业有着采购成本高、供应商数量多的特点,针对相关企业在进行供应商评价时,指标过于单一、评价方法过于主观、难以对供应商作出全面客观的评价等问题,在问卷调查的基础上,运用因子分析法对选择的指标进行筛选,构建适用于船用柴油机制造企业的供应商评价指标体系。将BP神经网络与遗传算法结合,建立基于GA-BP神经网络的供应商评价模型,并通过实例分析验证了模型在船用柴油机制造企业供应商评价中的有效性。

According to the characteristics of high procurement cost and large number of suppliers for marine diesel engine manufacturers, and the indicators are too single for the relevant suppliers in the evaluation of suppliers, the evaluation method is too subjective, which make it difficult to develop a comprehensive and objective evaluation of suppliers. On the basis of the questionnaire survey, the factor analysis method was used to screen the selected indicators, and a supplier evaluation index system suitable for marine diesel engine manufacturers was constructed. The BP neural network and genetic algorithm are combined to establish a GA-BP neural network based supplier evaluation model. The effectiveness of the model in the evaluation of supplier of marine diesel engine manufacturing enterprises is verified with an example.