BP神经网络及其在供应商选择评价中的应用

On the BP Neural Network and its Application in Supplier Selection and Evaluation

供应商选择评价方法是否得当,将直接决定企业所选供应商的优劣,并将最终影响到整个供应链的竞争能力。首先基于21世纪采购环境的变化及其对采购供应提出的新要求,结合前人的研究成果,构建了供应商选择评价指标体系,并对这些指标的内涵进行了分析。考虑到供应商选择指标之间呈现出复杂的非线性关系,而诸多的评价方法中,唯有人工神经网络具有独特的非线性适应性信息处理能力,据此论文以此为工具,运用前向神经网络中的BP神经网络设计了一套算法,并基于该算法建立了供应商选择评价模型,最后进行了实例分析。结果表明,运用这一评价模型来选择应商,能较好地避免其他方法人为计取权值和相关系数过程中的主观影响和不确定性,选择的结果比较客观、科学。

An appropriate method of supplier selection and evaluation will directly determine the quality of the suppliers selected by the enterprise,and ultimately affect the competition ability of the whole supply chain.Firstly,based on the changes to purchasing environment and the new requirements proposed for purchasing in the 21st century,with the achievements of previous researches,this paper presents a system of supplier selection of evaluation,and analyses the connotation of these indicators.Considering the complex nonlinear relations among the supplier selection indicators,the artificial neural network is the only method that enables nonlinear adaptive information processing in all methods.Thus,this paper designs a set of algorithms by using the BP neural network in the feed forward ones,and builds up an evaluation model followed by the analyzed examples.The findings show that this evaluation model to select supplier can be relatively objective and scientific,avoiding some subjective influence and uncertainty in the process of artificially taking weights and correlation coefficients by the other methods.