本論文旨在根據我們所提之區間直覺模糊值之新的得分函數、區間直覺模糊值的冪運算子、及加權式決策矩陣提出一個新的多屬性決策方法。本論文所提出的區間直覺模糊值之新的得分函數是基於區間之Beta分佈的區間期望值所建構的，其可以克服目前已存在之區間直覺模糊值之得分函數的缺點。首先，我們根據所提之區間直覺模糊值之新的得分函數及每一個屬性之區間直覺模糊權重以計算得到每一個屬性的精確值權重，進而得到每一個屬性之正規化權重。然後，我們根據區間直覺模糊值之冪運算子、所得到之每一個屬性之正規化權重、及決策矩陣以建構加權式決策矩陣。然後，我們根據所得到之加權式決策矩陣及所提之區間直覺模糊值之新的得分函數以建構分數矩陣。然後，我們根據所得到之分數矩陣以計算每一個方案之得分。最後，我們根據所得到之每一個方案之得分以對每一個方案作排序。如果一個方案有較高之得分，則此方案具有更佳之偏好排序。我們所提之多屬性決策方法可以克服目前已存在之多屬性決策方法之缺點，其在區間直覺模糊值之環境中提供我們一個非常有用的方法以作多屬性決策。

In this thesis, we propose a new score function of interval-valued intuitionistic fuzzy values and propose a new multiattribute decision making method based on the proposed score function of interval-valued intuitionistic fuzzy values, the power operator of interval-valued intuitionistic fuzzy values and the weighted decision matrix. The proposed score function of interval-valued intuitionistic fuzzy values is based on expected values of intervals using the beta distribution, which can overcome the drawbacks of the existing score functions of interval-valued intuitionistic fuzzy values. Firstly, we computes the crisp weight of each attribute based on the proposed score function of interval-valued intuitionistic fuzzy values and the interval-valued intuitionistic fuzzy weight of each attribute to obtain the normalized weight of each attribute. Then, we construct the weighted decision matrix based on the power operator of interval-valued intuitionistic fuzzy values, the normalized weight of each attribute and the decision matrix. Then, we construct the score matrix based on the obtained weighted decision matrix and the proposed score function of interval-valued intuitionistic fuzzy values. Then, we compute the score of each alternative based on the obtained score matrix. Finally, we rank the alternatives based on the scores of the alternatives. The larger the score of an alternative, the better the preference order of the alternative. The proposed multiattribute decision making method can overcome the drawbacks of the existing multiattribute decision making methods. It provides us a very useful approach for multiattribute decision making in interval-valued intuitionistic fuzzy environments.

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