工业工程

工业工程 ›› 2014, Vol. 17 ›› Issue (3): 114-120.

• 实践与应用 • 上一篇    下一篇

报废汽车回收再制造企业特征属性与生产性服务需求匹配预测

  

  1. 1.上海交通大学 工业工程与物流工程系,上海 200240；2.上海交通大学 中美物流研究院, 上海 200240；3.江苏天奇物流系统工程股份有限公司, 江苏 无锡 214187
  • 出版日期:2014-06-30 发布日期:2014-07-14
  • 作者简介:庞金茹（1989-），女，内蒙古自治区人，硕士研究生，主要研究方向为服务型制造.
  • 基金资助:

    国家自然科学基金资助项目（70932004）

Prediction of Feature Matching Between End-of-Life Vehicle Recycling and Remanufacturing Manufacturers and Producer Service Demand

  1. 1.Department of Industrial Engineering and Logistics Management, Shanghai Jiao Tong University, Shanghai 200240, China; 2.SinoUS Global Logistics Institute, Shanghai Jiao Tong University, Shanghai 200240, China; 3.Jiangsu Miracle Logistics System Engineering Co. Ltd. Wuxi 214187, China
  • Online:2014-06-30 Published:2014-07-14

摘要： 为了应对报废汽车回收再制造行业的快速发展，将报废汽车回收再制造产业链与生产服务相结合，提出将报废汽车回收再制造企业特征参数与多种生产性服务进行匹配的预测模型。通过调查问卷方式获得原始样本数据，并采用主成分分析方法进行数据处理，建立遗传算法BP神经网络混合模型，然后对模型进行训练和测试，实现对生产性服务需求匹配的预测功能。

关键词: 报废汽车回收再制造, 特征属性匹配, 生产性服务, BP神经网络, 遗传算法

Abstract: With the rapid development of the China automobile recycling and remanufacturing market, a BP neural network and genetic algorithm mixed model for featuring matching between end-of-life vehicle recycling and remanufacturing manufacturers and producer service demand is presented. On the basis of ascertaining the feature parameters and collecting data through questionnaire, principal component analysis is used to eliminate information overlapping of the raw data and reduce the input dimension. Then, a prediction model of genetic algorithm-BP neural network is proposed and finally used for training, testing data and predicting manufacturers-service demand.

Key words: end-of-life vehicle recycling and remanufacturing, feature matching, producer service, BP neural network, genetic algorithm