臺灣博碩士論文加值系統

人們面對各種問題總是有眾多的影響因素，如何從眾多影響因素中篩選出對自己最重要的影響因素，已經成為一個很重要的決策問題。多層級分析法(Analytic Hierarchy Process,AHP)是一種廣為應用在多準則決策問題的分析方法，決策的問題可以包含社會、政治、經濟等多種層面，利用階層化的結構來考量及評估單一問題的眾多影響因素，並且能夠量化決策之數值，清楚的說明選擇的理由。
本研究以VB.NET 開發多準則決策分析系統，並以多層級分析法為基礎，搭配分群、敏感度分析為輔助的客觀決策系統。由於判斷的層次標準都表現在系統的層級結構上，決策者可以融合自身的問題層次並做出重要的判斷，在系統決策結束之後，決策者可藉由匯出的功能明白決策是如何產生的以及相關決策因素之權重數值，此外，本研究還加入了模糊計算的功能，使決策者可以設定不同的模糊權重做矩陣的運算，進而得到更符合考量的答案。

There is always a large number of factors when people face a variety of problems, How to filter out from a number of factors for their most important factors, it has become a very important decision problems. Analytic Hierarchy Process(AHP) is a widely used method in the analysis of multi-criteria decision making problems, issues decisions can contain multiple levels of society, politics and economy, using class structure to consider and evaluate many factors of single problem, and can be quantified the value of decision, it is clear rationale for their choice.
In this study, the multi-criteria decision analysis system is developed by VB.NET, it based on the Analytic Hierarchy Process , with the grouping, sensitivity analysis for the secondary objective decision-making system. Due to judge the level of standards appear on the hierarchy system, decision makers can integrate their own problems and make significant judgments, at the end of the system decision, decision makers can understand how decisions are generated and a weight value related to the decision-making factors by export function, in addition, this study also joined the fuzzy Analytic Hierarchy Process(FAHP), so that decision makers can set different fuzzy weight to do matrix operation, then get more consistent with considerations of answers.

摘要 i
ABSTRACT ii
致謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
第二章 文獻探討 3
2.1 層級分析法(AHP) 3
2.1.1 AHP 發展目的與假設 4
2.1.2 AHP 法使用流程 6
2.1.3 AHP 法適用範圍 12
2.1.4 AHP 法的優劣比較 12
2.2 模糊層級分析法(Fuzzy AHP) 13
2.2.1 模糊理論 14
2.2.2 Fuzzy AHP法的優勢 16
2.3 敏感度分析(Sensitivity Analysis) 16
第三章 系統架構與設計 18
3.1 系統架構 19
3.2 系統流程圖 22
第四章 系統開發實作與優化 24
4.1 多語系 24
4.2 專家分群 26
4.3 問卷匯出與匯入 36
4.4 整體層級一致性檢定 40
4.5 決策匯出功能 41
4.6 敏感度分析 46
4.7 系統優化介紹 48
第五章 結論與展望 49
參考文獻 51

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