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Product-service supplier pre-evaluation with modified fuzzy ANP reducing decision information distortion

机译：产品 - 服务供应商预先评估修改模糊ANP减少决策信息失真

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摘要

The main challenge of new product-service supplier (PSS) selection is the lack of historical performance information of the suppliers. As one of the most popular techniques in supplier evaluation, the analytic network process (ANP) has an advantage in organising and analysing PSS pre-evaluation problems. However, the decision information distortion caused by matrix revision is a major factor affecting the wide application of the ANP when the consistency of the comparison matrix is unqualified. In this paper, a modified fuzzy ANP (F-ANP) with six criteria and 20 sub-criteria is suggested for PSS pre-evaluation. With the purpose of reducing decision information distortion in the pre-evaluation, the geometric scale is employed to improve the consistency of the judgment matrices and a linear approach is proposed for the unqualified judgment matrix revision. It is the first time that the decision information in the comparison matrix can be evaluated and retained as much as possible in generating and selecting the substitute using the proposed linear approach. The improved F-ANP model is verified in a real-life case study. Compared with the approaches in the literature, the linear approach shows advantages in retaining original decision information and the improved F-ANP outperforms the ANP and analytic hierarchy process models in terms of obtaining a stable rank of suppliers and distinguishing the importance of the criteria.
机译：新产品 - 服务供应商（PSS）选择的主要挑战是缺乏供应商的历史表现信息。作为供应商评估中最受欢迎的技术之一，分析网络过程（ANP）在组织和分析PSS预评估问题方面具有优势。然而，由矩阵修订引起的决策信息失真是影响比较矩阵的一致性不合格时ANP的广泛应用的主要因素。本文提出了一种具有六个标准和20个子标准的改进的模糊ANP（F-ANP），用于PSS预评估。通过降低预评估中的判决信息失真的目的，采用几何比例来提高判断矩阵的一致性，并且提出了用于不合格判断矩阵修订的线性方法。首次首次在使用所提出的线性方法中产生和选择替代品时可以尽可能多地评估和保留比较矩阵中的决定信息。改进的F-ANP模型在真实案例研究中验证。与文献中的方法相比，线性方法显示了保持原始决策信息的优点，并且改进的F-ANP在获得稳定的供应商等级并区分标准的重要性方面优于ANP和分析层次结构模型。

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