在一般的定義下，距離為衡量物體遠近的工具，而從另外一個角度來看，可將點與點間或是圖形間的距離視為一種衡量相似度的工具，若距離越近，則表示彼此間的相似程度越高、差異越小，反之亦然。本研究主要為利用八個距離測度公式，分別運用於群體意見的整合與相似度的衡量兩大方面。在本研究的第一部份將結合α截集與距離測度的概念，提出新的整合群體意見模式，之後以共識值到各專家意見之左右側距離比值為評估指標，分別考慮模糊意見具權重及不考慮模糊意見具權重兩情況，利用兩組文獻數據，從欲研究的八個距離測度中，篩選出表現較好的距離測度公式。而後以共識值到各專家意見之左右側距離比值為指標，利用兩組既有文獻資料，將本研究所篩選出的距離測度公式與過去學者提出的群體決策方法做出比較。
　　而本研究的第二部分則是提出一結合α截集與距離測度概念的衡量相似度模式，並利用21種具有代表性的模糊數組合，將本研究所提出的新方法與既有的相似測度做比較，研究結果證明本研究所提方法能夠真正解決這些現存方法所無法處理的狀況。

　　The distance measures are usually used as the similarity indicators in the pattern recognition. The objective of this research is to investigate the feasibility of eight existing distance measures in the aggregation of group fuzzy decisions and in the similarity measurement of two fuzzy numbers. In the first part of this research, we apply the concepts of α-cuts in each distance measure, and determine an optimal group fuzzy consensus based on mathematical theorems, representing the aggregation of individual fuzzy opinions. The ratio of the left distance to the right distance between the group fuzzy consensus and all individual opinions is developed to evaluate the quality of group fuzzy consensus. Using two datasets from the existing study and considering both weighted and original individual fuzzy opinions, the quality of group fuzzy consensus from eight distance measures is compared based on the proposed ratio. The best distance measure is adopted to compare with the existing aggregation methods of group fuzzy decisions.
　　In the second part, we also apply the concepts of α-cut to distance measure in measuring the degree of similarity between two generalized fuzzy numbers. The proposed method is demonstrated by comparing with the existing similarity measures using twenty-one sets of paired fuzzy numbers. The results show that the proposed similarity measure is better than the existing methods.

王小藩，多準則決策分析，滄海書局，民國94年。

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