理想解相似度順序偏好法(Technique for Order Preference by Similarity to Ideal Solution；TOPSIS)是一項用來處理多屬性決策問題的工具，透過明確性資料與距離的衡量對可行方案作出排序。但決策通常包含主觀的偏好，明確性資料無法完全適用於現實生活中的問題，且屬性評估值並非能夠完整呈現決策者內心真實的感受，而隨著決策的範圍擴大，過去一位決策者分析決斷的模式已漸漸不敷使用，另外模糊數之間的距離衡量眾說紛紜，沒有適當合理的衡量方式。針對上述問題，本研究在多屬性決策問題中加入群體決策與模糊集合理論的概念，建構出模糊環境下兩階段的群體決策之TOPSIS流程。第一階段中考慮模糊評估值以及各決策者的滿意度函數，再以類似群體投票的方式對方案作篩選，加強後續決策之品質；第二階段中考慮模糊數之距離衡量，求出方案的接近係數（closeness coefficient）後，再配合決策者的決策權重以加權平均的方式整合後再進行排序。此流程能夠呈現決策者主觀感受的滿意度值，打破傳統TOPSIS中屬性績效值單調遞增遞減的限制，以模糊評估值處理資訊不明確的狀況，並修正模糊數距離衡量的方式，使結果較為合理而有根據，另外加入了群體商議的過程，使決策結果較完整與周延。本研究以人力資源招募的例子，演算流程的每個步驟並求出排序結果，再與Shih et al.（2007）所提出之流程進行比較與分析，驗證本研究流程之優勢與彈性。

“Technique for Order Preference by Similarity to Ideal Solution；TOPSIS” is a useful tool for dealing with multi-attribute decision-making (MADM) problems. It can analyze and determine the ranking for all the alternatives based on crisp data and distance measurements. However, decision-making usually includes subjective preferences, and the decision maker’s real feelings can’t be completely revealed with performance ratings. When the scope of decision-making broadens, relying on only one decision maker’s judgment is deficient. In addition, the distance measurement of fuzzy data is not calculated reasonably. To address these problems, we add group decision-making and fuzzy sets theory into multi-attribute decision-making and construct a two-stage group decision-making TOPSIS process under a fuzzy environment. This decision process not only reveals decision makers’ subjective satisfaction degrees, but also breaks the restriction of monotonically increasing and decreasing performances. Moreover, it includes fuzzy ratings to deal with ambiguous situations and modifies the distance measure of fuzzy numbers to make the calculations more reasonable. We also add a group discussion process to make the results even more complete. Finally, a numerical example is performed using the proposed the decision-making process to demonstrate its superiority and flexibility compared to other processes.

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