Logistics Company Performance Evaluation by BP Neural network and DEA
In the process of evaluation logistics company performance by BP neural network, the more difficult problem is to determine the evaluating sample expectations, while the C2R.DEAcrossevaluation model is able to identify the rank and grade of evaluating samples (the unit of making decision). In this paper, we set the crossmodel evaluation results to the sample expectations, integrate BP neural network with crossevaluation model and construct the performance evaluation model of the logistics company, and use 23 Chinese logistics companies in 2007 as samples to carry out an empirical study. The results show that evaluation results are consistent with the actual situation, and the comprehensive weights reflect the degree of the performance indicators’ influence basically.
logistics companies performance evaluation BP neural network DEA crossing-evaluation model
Cheng-dong Shi Dun-xin Bian Cun-shan Zhang
School of Electrical and Electronic EngineeringShandong University of TechnologyZibo, Shandong,25509 School of Electrical and Electronic EngineeringShandong University of TechnologyZibo, Shandong, 2550 School of Electrical and Electronic Engineering Shandong University of Technology Zibo, Shandong, 25
国际会议
成都
英文
1-4
2010-04-16（万方平台首次上网日期，不代表论文的发表时间）