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Study on Supplier Selection and Evaluation in Serviced-oriented Manufacturing Network Based on NN

机译:基于NN的维修型制造网络供应商选择与评价研究

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The nature of service-oriented manufacturing network is modular service network for capacity need based. The difference in service capability increases the manufacturing networks' uncertainty, making the choice of supplier more complex. A strategy for supplier selection applying FWNN (fuzzy wavelet neural network) was presented in this paper. The first stage makes use of fuzzy system, with strong competency in knowledge representation, to convert fuzzy input parameters into crisp parameters. The artificial neural network was applied to overcome adverse effects resulting from supplier selection of non-liner and dynamic property in the second stage. The simulation was made to check the performance of the algorithm. The result indicates that this method can overcome the insufficiencies of subjectivity, arbitrariness, complicated algorithm and fuzzy input parameters in vendor selection, which realizes real-time dynamic evaluation and rapid selection under the service-oriented manufacturing environment, and its maximum relative error is less than 0.4841%.
机译:面向服务的制造网络的性质是基于容量需求的模块化服务网络。服务能力的差异增加了制造网络的不确定性,使供应商更加复杂的选择。本文提出了一种应用FWNN(模糊小波神经网络)的供应商选择策略。第一阶段利用模糊系统,具有知识表示的强大能力,将模糊输入参数转换为清晰的参数。应用人工神经网络以克服供应商选择在第二阶段中的非衬垫和动态特性产生的不利影响。进行了模拟以检查算法的性能。结果表明,该方法可以克服供应商选择中的主观性,任意,复杂的算法和模糊输入参数的不适当,从而实现了面向服务的制造环境下的实时动态评估和快速选择,其最大相对误差较少超过0.4841%。

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