決策問題通常包含多個面向，因此可從多個屬性去評估方案的表現，並讓多位專家一同討論和參與決策，而隨著時間變動，各方案的表現以及條件都可能有所改變，為了同時考量過去和現在的表現，可將多個時期的評估值整合起來做決策。此外，專家的意見通常具有主觀性和不確定性，以直覺式模糊數做為評估值將可以包含正負向資訊和猶豫程度。本研究提出一直覺式模糊動態群體決策模式，透過計算方案的表現在多期以來的變化趨勢對評估值做調整，利用相似度計算專家間的共識程度，並針對專家、方案和屬性的變動提出應對的方法，一步步整合各專家意見、各時期評估值和各屬性的表現去找出長期以來表現最佳的方案。多位專家透過多個屬性評估可以做出更全面客觀的決策，其中利用相似度計算共識程度以避免有過於偏差的專家意見影響決策結果。此外，考量專家、方案和屬性等條件的變動情況將更符合實際情形，且透過計算變化趨勢期望可以選出在多期以來表現較佳，且未來也會表現較佳之方案。最後對決策模式和共識程度分別進行範例演算，在決策模式的部分，發現本研究考慮趨勢變化的排序結果比起過去文獻更能在方案的排名反映出進步和退步的情形，更有助於找出最佳的方案；而共識程度的演算結果顯示本研究比起過去文獻的方法可更精確地找出明顯偏差評估值。

When people are making decisions, they evaluate all available alternatives with respect to different attributes. Decision-makers can benefit from inviting experts of different fields to evaluate the selected alternatives. With time, the number of alternatives, experts, attributes, and even the performance of alternatives change. In order to consider the temporal changes in the performance of several alternatives, we can use the so called dynamic decision-making method. In our model, we use similarity measure to calculate the consensus level between experts. This way we can avoid deviation evaluation values, which are too different from the other evaluation values and need to be modified, and we can also provide a standard threshold for decision-makers. Obtaining the trends of alternatives’ performances over these periods, we can modify the evaluation values of alternatives as well. Our model aggregates the evaluation values of each alternative with respect to each attribute provided by different experts in each time period. Through the above processes, we hope to find the alternative that had the best performance in the past and will most likely perform even better in the future. Finally, we compare our proposed model with the literature. We found that our model reflects the trends of the alternatives’ performances more reliably than methods of literature. The result from our consensus level model showed that our model could find out the deviation values more precisely.

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