模糊數排序在決策分析與應用上佔有重要的地位，故近數十年來，專家學者提出了許多模糊數排序方法，例如最大集合與最小集合、積分值、中心點、距離、偏離程度及尺度等觀念。然而這些方法之中，有些並不符合直覺，甚至有不一致的情形。因此，本研究指出這些既有方法中的缺陷，並且提出能改善這些缺陷的模糊排序方法。
本研究進一步利用所提出的模糊數排序方法，發展模糊多準則決策模型以支援醫療服務提供者的評估及選擇。在此模型中，醫療服務提供者的評分及準則的重要程度先以語意項目表示，接著再建立最終模糊評估值的成員函數。為了使本模型更加實用及易於應用，本研究應用所提出的模糊排序方法，將正規化後的加權評分解模糊化，得到明確數值，以建立醫療服務提供者的排序。本研究還採用了數值例子，以證明所提出的多準則決策模型的適用性和優點。

Ranking fuzzy numbers plays an important role in decision analysis and applications. The last few decades have seen a large number of approaches investigated for ranking fuzzy numbers such as maximizing set and minimizing set concept, integral value, centroid point, distance approach, deviation degree, and magnitude concepts. Nevertheless, some of these approaches are non-intuitive and even inconsistent. Therefore, this study indicates the shortcomings of several existing ranking approaches and proposes improved ranking approaches for fuzzy numbers to overcome their shortcomings.
Based on the proposed ranking approaches, an extension of fuzzy multi-criteria decision making is developed for supporting the medical provider selection and evaluation selection process. In the proposed fuzzy multi-criteria decision making model, the ratings of alternatives and importance weight of criteria for medical providers are expressed in linguistic terms. This study then can also obtain the membership functions of the final fuzzy evaluation value in the proposed model. To make the procedure easier and more practical, the normalized weighted ratings are defuzzified into crisp values by using the improved ranking approaches to determine the ranking order of alternatives. This study also uses a numerical example to demonstrate the applicability and advantages of the proposed multi-criteria decision making model.

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