多準則決策(Multiple Criteria Decision Making)與群體決策(Group Decision Making)是決策科學中兩個主要的研究領域。Saaty(1980)提出的層級分析法(Analytic Hierarchical Process, AHP)是一種多準則決策的方法，在文獻中已有很多研究將其廣泛地應用在不同領域的決策問題上，並獲致良好的成效。而在將層級分析法延伸至群體決策時，到目前為止，研究主要集中如何整合群體決策的問題上，算術加權平均法與幾何加權平均法是文獻中最普遍使用的整合模式。但就這樣子的應用而言，仍有兩方面的議題值得進一步改善：一項是進行加權平均時，各決策者的權重值如何決定，目前文獻中尚未有共同認可的方法；另一項則是僅以簡單的數學平均公式來整合決策者的意見，顯得過於單純化，而且平均法容易受到極端值影響的缺點仍然存在。因此，本研究將就層級分析法在群體決策問題的應用上，針對上述兩項議題分別提出：

(1)以模糊積分(Fuzzy Integral)為基礎的決策整合模式，提供一非線性的決策整合方法，降低極端值對整合決策值的影響。
(2)以「決策者信心程度」為基礎的決策者權重決定模式，提供加權平均法所需要的權重值。此外，並將信心程度導入層級分析法中，發展一新的模糊層級分析法模式，可同時解決不平衡尺度問題並改善決策的「不明確」情況處理能力。

　Multiple Criterion Decision Making (MCDM) and Group Decision Making (GDM) are two major disciplines of decision science. The analytic hierarchical process (AHP) method is one of the most popular MCDM methods. Since the AHP approach was proposed (Saaty, 1980), the literature has presented numerous discussions and applications, most of which have reached positive conclusions. Some studies have discussed AHP in GDM environments and focused on the issues involved in aggregating group decision. The weighted arithmetic mean method (WAMM) and the weighted geometric mean method (WGMM) are the two most popular techniques for aggregating group decisions. However, there are two disadvantages existed in WAMM and WGMM: one is how to determine the weights of decision makers (DMs) in WGMM and WAMM, and the other is that WGMM and WAMM are both simple methods for aggregating group decisions and their result is sensitive to extreme values. Therefore, this study attempts to make the following two contributions:
1.Proposes a fuzzy-integral based group decision　aggregation model. This model provides a nonlinear function for aggregating group decisions and avoids the effect of extreme values.
2.Present a model for determining the weights of DMs based on their assurance levels.Furthermore, assurance level is introduced to AHP to yields a fuzzy AHP model that resolves the problem of unbalanced scale of AHP and improves ambiguity in decision-making.

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