臺灣博碩士論文加值系統

由於決策環境的不明確，加上決策過程中包含太多不確定的判斷，所以績效評估往往是在不同的決策風險下進行，而相關的評估值，也不像傳統方式以確定的評估值表示，而是以不確定的區間值來取代明確數(crisp number)。雖然模糊加權平均法(FWA)已大大改善了傳統績效評估的缺點，但其假設加權分(weighted rating)間之結合（connective）是呈線性加法(linear addition)的關係，實際上它會依據決策者之決策行為而有所變動。因此本研究將應用群體參與決策，彙集各專家學者意見，避免單一決策者的主觀判斷，增加決策結果的客觀性且利用模糊理論，在準則權重、準則評分及加權分間之結合，三者全為模糊假設，全部建立在模糊數(fuzzy number)上，找出模糊加權通用平均式(FWGM)之p值，來瞭解決策者之決策行為模式，使其更符合現實環境的情況。

Because of the decision making condition is usually not defined and the decision making process also contains many uncertainties. So the performance evaluation always carries out in different risk condition. It correlates evaluative value is different from the traditional performance evaluation expressed by certain evaluative value. It utilizes uncertain interval value instead of crisp number. Although Fuzzy Weighted Average (FWA) has already improved the defect of the traditional performance evaluation. But FWA assumes the connective between weighted rating is linear addition. Actually the connective between weighted rating will variety bases on decision maker''s behavior. This thesis utilizes group decision making and gathers their opinions of experts. We utilize fuzzy theory for avoiding the dictatorship of single decision maker and increase the objectivity of decision making''s result. Criteria weighting, criteria rating and the connective between weighted rating are all fuzzy assumption. They all set up at fuzzy number. Then we find out the value p of Fuzzy Weighted Generalized Mean (FWGM) to understand the decision maker''s behavior and accord with the realistic situation.

第一章 緒論
1-1 研究背景與動機
1-2 研究目的
1-3 研究方法
1-4 研究架構與步驟
第二章 文獻回顧（一）：模糊理論
2-1 模糊集合
2-2 a - 截集
2-3 模糊數
2-4 模糊矩陣
2-5 模糊計算
2-6 集成運算
第三章 文獻回顧（二）：模糊加權平均法
3-1 F''WA法
3-2 IFWA法
3-3 PFWA法
3-4 Charnes and Cooper''s 線性轉換法
第四章 模糊加權平均法之模糊結合問題模式建立
4-1 層級評估架構之構建
4-2 決定模糊準則評分
4-3 決定模糊準則權重
4-4 決定決策者對受評者之績效指標目標值
4-5 決定加權分間之結合方式 --- p值決定
4-6 舉例說明
第五章 實例應用 --- 教師績效評估
5-1 評估準則項目決定及層級評估架構之構建
5-2 準則權重設定
5-3 模糊準則權重計算
5-4 準則評分
5-5 模糊準則評分計算
5-6 受評者之績效指標目標值
5-7 受評者之績效指標目標值計算
5-8 加權分間之結合方式 --- p值決定
第六章 結論與後續研究
6-1 結論
6-2 後續研究

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