基于模糊粗糙集与多专家网络层次分析法的整车质量评价模型及算法研究

Research on Quality Evaluation Model and Algorithm Based on Fuzzy Rough Set and Multi-expert Analytic Network Process

汽车产业链云服务平台的汽车质量评价是一个多目标评价问题,质量评价影响因素之间相互联系又相互制约,而且具有明显的不确定性、模糊性。针对这一问题采用定性和定量相结合的方法,为了提高评价结果的准确性和客观性,提出一种基于模糊粗糙集和多专家网络层次分析法(ANP)的质量评价数学模型。运用改进的模糊粗糙集计算指标的客观权重,利用多专家ANP方法确定指标的主观权重,再综合主客观权重,采用模糊综合评价法得出最终评价结果,并应用于凯马整车制造企业的汽车质量评价中。最后通过实例验证了评价模型的合理性、有效性和可靠性。

Based on the automobile industry chain, the automobile quality evaluation is a multi-objective evaluation prob- lem, seeing that influence quality factors are interconnection and interaction, which possess uncertainty and fuzziness obvi- ously,in view of this question, the article used a combination of qualitative and quantitative methods. In order to improve the accuracy and objectivity of the evaluation results, a mathematical model of fuzzy rough set combined with multi-expert Analytic Network Process （ANP） is proposed, multi-expert Analytic Network Process （ANP） method combined with modified fuzzy rough set in the comprehensive weighting method to determine index weight, fuzzy comprehensive evalua- tion method to get the results of the assessment, which is applied to automobile quality evaluation in the Kai Ma vehicle manufacturing enterprise. Finally, an example is given to verify the rationality, validity and reliability of the evaluation model.