基于优化神经网络的云计算环境下供应链伙伴选择

针对云计算环境下供应链伙伴的动态性,提出一种基于优化神经网络的云计算环境下供应链伙伴选择模型.首先构建计算环境下供应链伙伴评价指标体系,并采用层次分析法计算每一个指标的权值,然后采用神经网络对采集的企业评估训练样本进行学习,并采用遗传算法对神经网络参数进行优化价,建立企业综合评估模型,最后进行了仿真模拟实验.结果表明,本文模型可以准确描述供应链伙伴的动态性,能够对云计算环境下的供应链伙伴进行全面、公正的评价.

Supply Chain Partner Selection Based on Optimizing Neural Network in Cloud Computing

Aiming at the dynamic supply chain partners in the cloud computing environment, this paper puts forward a supply chain partner selection based on optimizing neural network in cloud computing. Firstly, evaluation system of supply chain partner is constructed in cloud computing environment, and every index weight of is calculating by analytic hierarchy process, and then neural network is used to evaluate enterprise based on training samples, while genetic algorithm is used to optimize the parameters of neural network and to establish evaluation model of enterprise, finally, the simulation experiment is used to test the performance. The results show that the proposed model can accurately describe the dynamic change of supply chain partners. It also can comprehensive evaluate supply chain partners under the cloud computing environment.