With the vigorous development of the global economy, modern enterprises have agreed to implement green supply chain management. The evaluation and selection of green suppliers plays a vital role in successful green supply chain management. As a multi-attribute group decision-making green supplier selection problem, it is difficult to fully describe the evaluation factors using precise numerical values and classical fuzzy sets, so it cannot assist enterprise managers in making completely reasonable decisions. Therefore, this paper proposes a green supplier evaluation and selection method based on interval BPA-based intuitionistic fuzzy sets. First, build a green supplier evaluation index system based on the characteristics of the papermaking enterprise's suppliers. Then, the intuitionistic fuzzy number is used to express the indicators of the evaluator for each supplier, and the intuitionistic fuzzy information is integrated through the organic combination of the IIFWA integration operator and the structural entropy weight to obtain the comprehensive evaluation value of the evaluator. Finally, the interval BPA-based intuitionistic fuzzy set method ranks the candidate suppliers and determines the best green supplier. Applying this method to the field of green supplier evaluation and selection can provide an effective method for enterprises to select suppliers scientifically and reasonably, which has practical reference value and practical significance.

To evaluate the investment decisions of new energy vehicle enterprises scientifically and reasonably and improve the investment efficiency and accuracy of decision-makers, this paper proposes an investment decision method based on interval intuitionistic fuzzy sets. In the investment decision-making process of new energy vehicle enterprises, first, based on the characteristics of new energy vehicle enterprise investment projects, an index system is constructed to comprehensively cover the influencing factors of investment decisions. Second, we obtain the interval fuzzy number of the decision index through a questionnaire survey, use the structural entropy method to empower decision indicators, and comprehensively evaluate the decision index by the organic combination of the interval-valued intuitionistic fuzzy weighted averaging (IIFWA) operator and structural entropy method. Finally, interval BPA is used to express the value of each decision index interval intuitionistic fuzzy number. Based on the conversion relationship between interval evidence and the intuitionistic fuzzy set, the orthogonal sum operation results of the intuitionistic fuzzy set converted from the normalized interval BPA is replaced by the interval evidence combination result, and the final decision is determined by comparing the fusion result. Applying the investment decision method based on interval intuitionistic fuzzy sets to the field of new energy vehicle investment decision-making can provide a reference for investment decision-makers to make efficient and accurate decisions, and it has application value and practical significance to promote the effective development of new energy investment decisions.