長久以來，供應商選擇決策被視為是採購部門最重要的任務之一。在現實世界中，根據眾多不同的準則評選適當的供應商所導致大量的資料經常是不精確且具不確定性；而且，在許多真實複雜系統中的評估準則的數目，通常是太多以致於很難決定其獨立或相依關係。然而，大部分傳統決策模式卻未能對準則內之次準則間的相互關係有明確認定，僅假設其為加法性或獨立性。
因此，本論文提出三個研究議題來詳細探討，提出以關係圖為基礎之模糊多評準決策解決供應商選擇問題。第ㄧ個議題發展一個多準則最佳化妥協優勢排序法來選擇最適供應商，其中，利用模糊德爾非法決定各準則的模糊權重値；評選結果顯示當同時考量最大群體效用與最小個別遺憾時，本決策方法所決定之供應商將更具有權衡效果。第二個議題建構一個整合性模糊多評準決策方法解決供應商選擇問題，考慮過去文獻所忽略的準則間內部相依問題；採用明示結構模型(interpretive structural modeling; ISM)法建構一關係圖，去定義各準則內之次準則的獨立或內部相依關係；同時，運用非加法型模糊積分法得到各共同準則之模糊綜合績效值，此外，實務個案應用結果顯示本論文所提之方法較傳統方法更為合適，特別當現實情況中各次準則存在有內部相依關係。最後一個議題是運用決策評選實驗室(decision making trial and evaluation laboratory; DEMATEL)法去透視一系統中各準則間複雜因果關係的結構和獲得這些準則的相互干擾程度，進一步，藉由Saaty所提出之(analytical network process; ANP)去克服準則間內部相依與回饋的問題，雖然此法在處理上述問題是容易且有效的，但在此方法步驟中，使用平均法(即各群組同等權重)所得到加權後之超矩陣似乎不太合理，因為各準則間存在有不同的干擾程度影響。另外，本論文藉由理想點的概念，針對實務個案應用於改善各供應商使其減少在各次準則之實際績效值與理想目標值間的差距而達到最佳供應商，提供決策者一些有價值的建議。

Vendor selection decisions have been long considered one of the most important functions of the purchase department. In the real-world, selecting appropriate vendors should be considered and evaluated in terms of many different criteria resulting in a vast body of data that are often inaccurate or uncertain. Furthermore, the numbers of evaluation criteria in the real complex problems are often too large to determine dependent or independent relationships and there may be no solutions for satisfying all criteria to achieve the aspired level simultaneously. However, most conventional decision models cannot be considered for clarifying the interrelations among the sub-criteria of a criterion by virtue of additivity and independence assumptions.
For this reason, this dissertation is to determine three research topics to explore fuzzy multiple criteria decision making (MCDM) for solving vendor selection problem based on relation map. The first topic is to develop a MCDM optimization with compromise ranking methods to select appropriate vendor, in which a fuzzy Delphi method is applied to determine the weights of criteria. The evaluation results indicate the vendor has the trade-off effects while considering a maximum group gain (benefit) and a minimum individual regret (loss) for a company. The second topic is to formulate an integrated fuzzy MCDM technique for solving vendor selection problems. The interrelation between criteria that was ignored by previous researchers is considered in this dissertation. A relationship map to identify the independence or interdependence of the sub-criteria of a criterion is constructed by using interpretive structural modeling (ISM), and then the fuzzy synthetic performance of each common criterion can also be obtained by applying a non-additive fuzzy integral technique. In addition, the results of a practical application show that the proposed method is more suitable than traditional method, especially when the sub-criteria are interdependent in real situations. The third topic is to employ the decision making trial and evaluation laboratory (DEMATEL) method to visualize the structure of complicated causal relationships between criteria of a system and obtain the influence degree of these criteria. Furthermore, the analytical network process (ANP) method is proposed by Saaty to overcome the problems of interdependence and feedback between criteria. The general methods are easy and useful for conducting the problems above. But in ANP procedures, by using average method (equal cluster- weighted) to obtain the weighted supermatrix seem to be irrational because there are different influence degrees among the criteria. Further, by using the concept of ideal point in this dissertation, the results of a practical application could provide some valuable opinions to decision maker on improve each sub-criterion to reduce the gaps between real performance values and aspired/desired values to achieve the best vendor.

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