基于ANP-RBF神经网络的化工行业绿色供应商选择

摘要

Based on the philosophy of green supply chain management, this paper develops a green supplier selection, method of chemical industry, which is called ANP-RBF neural network hybrid model. It integrates analytic network process( ANP) and a novel and efficient artificial neural network; radial basis function ( RBF) neural network. Given both practicality in traditional supplier selection indexes and environmental factors, several distinctive indexes have been put forward and applied in ANP. During RBF neural network experimental procedure, implied knowledge is extracted from the training data and conveniently used in new supplier selection process. This is ah incremental algorithm. Hence, the model has scalability and can enhance the dynamic assessment a-bility. The empirical results indicate that the ANP-RBF neural network hybrid model is of great practical value for the green supplier selection of chemical industry.%基于绿色供应链理念,提出了化工行业绿色供应商选择的特色指标,构建了化工行业绿色供应商选择的ANP-RBF神经网络模型.通过ANP确定各指标权重,再结合RBF神经网络,从训练数据中提取隐含的知识和规律,能够方便地用于新供应商的选择.该模型求解算法为增量算法,具有很好的可扩展性,从而增加了评价的动态性.算例验证结果表明,将ANP-RBF神经网络模型用于化工行业绿色供应商的选择具有较强的实用性.