基于GA-BP神经网络的船用柴油机制造企业供应商评价
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摘要
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.
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.
引文
[1]顾钧琦.我国船用低速柴油机配套体系现状[J].船舶标准化与质量,2017(5):12-15.
[2]谭春平,王烨.面向供应链的供应商选择模型构建[J].统计与决策,2018,34(11):52-55.
[3]DICKSON G W.An analysis of vendor selection systems and decision[J].Journal of Purchasing,1966,2(15):1377-1382.
[4]WINTER S,LASCH R.Environmental and social criteria in supplier evaluation-lessons from the fashion and apparel industry[J].Journal of Cleaner Production,2016,139:175-190.
[5]FALLAHPOUR A,OLUGU E U,MUSA S N,et al.An integrated model for green supplier selection under fuzzy environment:application of data envelopment analysis and genetic programming approach[J].Neural Computing&Applications,2016,27(3):707-725.
[6]MIHOV A,NARANjO A.Customer-base concentration and the transmission of idiosyncratic volatility along the vertical chain[J].Journal of Empirical Finance,2017,40(1):73-100.
[7]郭媛媛,杨斌.基于低碳理念的绿色供应商选择模型[J].安徽工业大学学报(自然科学版),2013,30(2):208-212.
[8]郝国英,孔造杰.群体决策环境下的一种供应商选择方法[J].统计与决策,2016(15):49-51.
[9]LO H W,LIOU J J H,WANG H S,et al.An integrated model for solving problems in green supplier selection and order allocation[J].Journal of Cleaner Production,2018,190:339-352.
[10]刁柏青,张伟昌,王中龙,等.基于改进模糊综合评价法的电力供应商评价模型[[J].计算机系统应用,2018,27(5):226-231.
[11]周清华,王琦.基于直觉模糊集和VIKOR的低碳供应商选择方法研究[J].科技管理研究,2017,37(10):233-237.
[12]郜振华,梅莉.基于熵权系数与灰色关联分析的供应商评价方法[J].安徽工业大学学报(自然科学版),2012,29(3):280-284.
[13]徐先进.安庆中船柴油机公司供应链管理研究[D].合肥:安徽大学,2012:20-24.
[14]赵莉,赵艳萍,于惠敏.船舶制造企业供应商选择与评价体系研究:以镇江四洋柴油机制造有限公司为例[J].会计之友,2013(10):73-76.
[15]徐莉,李卓然.特高压输电线路工程造价预测模型研究:基于因子分析及BP神经网络[J].工业技术经济,2017,36(7):18-26.
[16]VASKE J J,BEAMAN J,SPONARSKI C C.Rethinking internal consistency in cronbach’s alpha[J].Leisure Sciences,2017,39(2):163-173.
[17]陈洪海,迟国泰.基于主要信息含量的指标筛选方法[J].系统工程学报,2016,31(2):268-273.
[18]叶云,赵小娟,胡月明.基于GA-BP神经网络的珠三角耕地质量评价[J].生态环境学报,2018,27(5):964-973.
[19]刘蕊蕊,于合谣,冀鹏飞.基于遗传算法改进的BP神经网络算法[J].德州学院学报,2017,33(4):38-41.
[2]谭春平,王烨.面向供应链的供应商选择模型构建[J].统计与决策,2018,34(11):52-55.
[3]DICKSON G W.An analysis of vendor selection systems and decision[J].Journal of Purchasing,1966,2(15):1377-1382.
[4]WINTER S,LASCH R.Environmental and social criteria in supplier evaluation-lessons from the fashion and apparel industry[J].Journal of Cleaner Production,2016,139:175-190.
[5]FALLAHPOUR A,OLUGU E U,MUSA S N,et al.An integrated model for green supplier selection under fuzzy environment:application of data envelopment analysis and genetic programming approach[J].Neural Computing&Applications,2016,27(3):707-725.
[6]MIHOV A,NARANjO A.Customer-base concentration and the transmission of idiosyncratic volatility along the vertical chain[J].Journal of Empirical Finance,2017,40(1):73-100.
[7]郭媛媛,杨斌.基于低碳理念的绿色供应商选择模型[J].安徽工业大学学报(自然科学版),2013,30(2):208-212.
[8]郝国英,孔造杰.群体决策环境下的一种供应商选择方法[J].统计与决策,2016(15):49-51.
[9]LO H W,LIOU J J H,WANG H S,et al.An integrated model for solving problems in green supplier selection and order allocation[J].Journal of Cleaner Production,2018,190:339-352.
[10]刁柏青,张伟昌,王中龙,等.基于改进模糊综合评价法的电力供应商评价模型[[J].计算机系统应用,2018,27(5):226-231.
[11]周清华,王琦.基于直觉模糊集和VIKOR的低碳供应商选择方法研究[J].科技管理研究,2017,37(10):233-237.
[12]郜振华,梅莉.基于熵权系数与灰色关联分析的供应商评价方法[J].安徽工业大学学报(自然科学版),2012,29(3):280-284.
[13]徐先进.安庆中船柴油机公司供应链管理研究[D].合肥:安徽大学,2012:20-24.
[14]赵莉,赵艳萍,于惠敏.船舶制造企业供应商选择与评价体系研究:以镇江四洋柴油机制造有限公司为例[J].会计之友,2013(10):73-76.
[15]徐莉,李卓然.特高压输电线路工程造价预测模型研究:基于因子分析及BP神经网络[J].工业技术经济,2017,36(7):18-26.
[16]VASKE J J,BEAMAN J,SPONARSKI C C.Rethinking internal consistency in cronbach’s alpha[J].Leisure Sciences,2017,39(2):163-173.
[17]陈洪海,迟国泰.基于主要信息含量的指标筛选方法[J].系统工程学报,2016,31(2):268-273.
[18]叶云,赵小娟,胡月明.基于GA-BP神经网络的珠三角耕地质量评价[J].生态环境学报,2018,27(5):964-973.
[19]刘蕊蕊,于合谣,冀鹏飞.基于遗传算法改进的BP神经网络算法[J].德州学院学报,2017,33(4):38-41.