## 1 Introduction
Different from the TOPSIS method, the ELECTRE method lays greater emphasis on sorting and assessing the relationship between the alternatives rather than simply calculating the distance. The VIKOR method [33] also determines the positive and negative ideal solutions and then judges the advantages and disadvantages of solutions according to the distance between the evaluation value of the solution to be selected and the ideal solution. All the above methods can effectively deal with multi-attribute decision problems, and their advantages and disadvantages and applicable scenarios are shown in Table 1. Upon a comprehensive consideration of the above methods, the TOPSIS method was selected and appropriately improved to carry out the relevant research work. The above-mentioned studies provide useful references for this study, but the current hesitation fuzzy set and its extended form are still insufficient in dealing with the multiple hesitancies and fuzziness of decision information. Especially in the process of multi-attribute decision-making, evaluation experts often hesitate about the degree to which a scheme satisfies a certain attribute. Multiple estimates may be needed to characterize this hesitancy on the part of the evaluator. Additionally, within the evaluation team, experts \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Advantages** & **Disadvantages** & **Applicable Scenarios** \\ \hline \multirow{4}{*}{TOPSIS} & 1. Intuitive and easy to understand. & 1. Sensitive to weight setting. & \\  & 2. It is widely applicable and can & 2. Not good at dealing with & \\  & reflect the overall situation of & high-dimensional data. & \\  & evaluation objects. & & \\ \hline \multirow{4}{*}{GRA} & 1. Convenient and practical with a & 1. Subjective in determining the & \\  & small, calculated quantity & optimal values of indicators. & \\  & 2. Able to analyze the relational & 2. Fais to reflect the overall situation & \\  & degree between various factors. & of the system. & \\ \hline \multirow{4}{*}{ELECTRE} & 1. Easy to understand and able to & 1. High cost of computational & \\  & quantity the decision process. & resources and time when handling & \\  & 2. Allows decision-makers to make & \\  & decisions based on known factors. & 2. High requirements for data quality & \\  & & and integrity. & \\ \hline \multirow{4}{*}{VIKOR} & 1. Multiple attributes or targets can be & \\  & considered at the same time. & \\ \cline{1-1}  & 2. It is suitable for solving decision & \\ \cline{1-1}  & problems with conflicting objectives. & \\ \cline{1-1}  & 3. The weight setting is more flexible. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Analysis of common decision methods. may not reach an agreement on the set of evaluation values and may hesitate between several possible evaluation value sets. This situation gives rise to multiple hesitations, which the existing hesitation fuzzy set and its generalized form cannot adequately describe or handle. Therefore, this paper proposes the concept of Type-2 hesitant Pythagorean fuzzy sets to process decision information from experts evaluating the support capability of civil aircraft spare parts. Firstly, this paper took the evaluation of civil aircraft spare parts support capability as the research object and constructed a practical evaluation index system of spare parts support capability. Secondly, the weight of each attribute was determined using the distance measurement formula and entropy measurement formula of the proposed Type-2 hesitant Pythagorean fuzzy sets. Then, the spare parts support capacity of civil aircrafts was assessed and sorted based on the correlation coefficient formula of Type-2 hesitant Pythagorean fuzzy sets and improved TOPSIS. Finally, the proposed method was proved to be scientific using calculation examples.