Combinative Distance based ASsesment (CODAS) method aims to perform multi-criteria selection process according to the largest Euclidean and Taxicab distance with respect to negative ideal solutions. Recently, several CODAS methods have been applied to multi-criteria decision making problems with interval valued intuitionistic fuzzy sets. This paper demonstrates the weaknesses of using Euclidean and Taxicab distance on interval valued intuitionistic fuzzy sets and provides alternative strategies to model the vagueness and uncertainty in decision maker evaluations more effectively. The contribution of this paper is twofold. First, a new selection metric is defined in order to eliminate the disadvantages of using Euclidean and Taxicab distance in interval valued intuitionistic fuzzy CODAS. Second, a new fuzzy aggregation operator is proposed for aggregating decision maker evaluations by using fuzzy weights rather than using crisp weights. To show the effectiveness of the modified CODAS method, an application is given for multi-criteria selection of renewable energy alternatives in Turkey and the results are compared with two other interval valued intuitionistic fuzzy CODAS methods in the literature.

基于组合距离的评估（CODAS）方法旨在针对负理想解决方案，根据最大的欧式距离和出租车距离来执行多标准选择过程。最近，几种CODAS方法已应用于具有区间直觉模糊集的多准则决策问题。本文演示了在区间值直觉模糊集上使用欧几里得距离和出租车距离的弱点，并提供了替代策略来更有效地建模决策者评估中的模糊性和不确定性。本文的贡献是双重的。首先，定义了一个新的选择度量，以消除在区间直觉模糊CODAS中使用欧式距离和出租车距离的缺点。第二，提出了一种新的模糊聚合算子，用于通过使用模糊权重而不是使用明晰权重来聚合决策者评估。为了显示改进的CODAS方法的有效性，在土耳其提供了一种用于多标准选择可再生能源的方法，并将结果与​​文献中的其他两种区间直觉模糊CODAS方法进行了比较。