多準則決策方法(Multiple Criteria Decision Making, MCDM)幫助決策者分析衡量可行方案，以制定出較佳的決策。然而，大部份的多準則決策方法著重於決策偏好的計算，而忽略如何取得這些偏好。這可能導致決策品質不佳的情形。基於認知心理學家凱利所提出之個人建構理論(PCT)，其中的凱利方格訪談法為一可靠知識擷取方法，能減少擷取過程的偏誤。本研究結合凱利方格訪談法，提出決策支援模型FRGAT，希望讓決策者表達出的偏好與其心中想法更一致。
FRGAT是一個多準則決策支援模型，從與決策者訪談開始，直到獲得每個方案的分數結束。首先，利用凱利方格訪談法取得決策者偏好資料，接著運用TOPSIS的正負理想解概念做為評估方案的原則。本模式也適用於群體決策情境。實證部分則以電信機房資源分配為例，最後並運用MAFA (mean absolute forecasting accuracy)進行結果討論。

Multiple Criteria Decision Making (MCDM) methods help decision makers to analyze and evaluate possible solutions in making a better decision. However, most MCDM methods focused on how to process ratings instead of how to access them. Less rigorous opinion retrieval procedures cause bias. The bias will have bad effects on final decision. Based on psychologist George Kelly’s Personal Construct Theory, repertory grid (RG) is a reliable knowledge acquisition method which can capture individual inside thoughts and reduce bias data. This study proposes a method-- fuzzy repertory grid analysis with TOPSIS (FRGAT). Ensuring ratings and the MCDM result accords with the decision maker's mind.
FRGAT is an MCDM support model, starts from interviewing with decision makers and ends up with the ranking of alternatives. First, we interact with decision makers with Fuzzy RG to get their thoughts on alternatives. Second, we use the concept of ideal solutions, originated from TOPSIS, as our evaluation principle. Each alternative will have its score and rank. The FRGAT model also can apply to group decision making scenario. Decision makers can take the score/rank result in their consideration when making the final decision. A telecommunication rooms' resource allocation problem was used to illustrate FRGAT step by step. Finally, MAFA (mean absolute forecasting accuracy) was used as a similarity measure in our discussions.

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