## 2 Research Methods
### Selection of Multi-Objective Decision-Making Methods  
Facing the Pareto frontier solutions derived from multi-objective optimization, decision theory is applied for further analysis and decision-making. Common decision theories include multi-criteria decision analysis (MCDA), group decision theory, and behavioral decision theory, among which MCDA is commonly used to assess multiple feasible solutions on the Pareto frontier. By weighing the importance of different objectives, MCDA can help decision-makers choose the most suitable solution. Common methods include the weighted sum method, the analytic hierarchy process (AHP), and the technique for order preference by similarity to the ideal solution (TOPSIS). When the results of multi-objective optimization require selection by a team or group, group decision theory can be chosen. Issues studied in group decision-making typically have characteristics of autonomy, coexistence, and consensus. Decision-makers have relatively independent decision-making power and choices, and their decisions or actions are not dominated by power factors, but there may be mutual constraints and influences between decision-makers and other group members. Additionally, members of group decision-making are considered as a whole. The outcomes or actions ultimately made by the group should be schemes that all group members can unanimously accept [73]. Commonly used methods, such as the Delphi method and majority voting, are employed to integrate the preferences of group members to achieve collective decision-making. [PERSON] and others used the analytic hierarchy process and the Delphi expert consultation method to establish an evaluation system for the energy-saving suitability of nearly zero-energy building envelopes in different climate zones [74]. Behavioral decision theory explores \"how people actually make decisions\" and \"why they make decisions this way\", starting with the Allais paradox in 1953 and the Edwards paradox in 1961 [75]. Behavioral decision theory emphasizes psychological factors in the decision-making process, applicable in multi-objective optimization scenarios where decision-makers can understand how they evaluate different solutions and explore the psychological mechanisms behind their preferences. In typical multi-objective optimization problems, no single solution can achieve the optimum for all performance indicators simultaneously; all non-dominated solutions are on the Pareto frontier. In this context, the entropy weight method, as an objective weighting method, plays an important role in multi-criteria decision analysis by eliminating the impact of subjective human factors and providing objective evaluation criteria [76]. It is used to determine the weights of various indicators by analyzing the variability of each indicator, effectively avoiding the subjectivity of weight determination and the problem of information overlap between multiple indicators. Facing the Pareto frontier solutions derived from multi-objective optimization, decision-makers need to apply appropriate decision theories for further analysis and selection. Common decision theories include multi-criteria decision analysis (MCDA), group decision theory, and behavioral decision theory. Among these theories, MCDA is particularly suitable for evaluating multiple feasible solutions on the Pareto frontier, allowing decision-makers to identify which schemes best meet their preferences by comparing the relative advantages of different solutions. Common MCDA methods include the weighted sum method, the analytic hierarchy process (AHP), and the technique for order preference by similarity to the ideal solution (TOPSIS), each with its own unique advantages and applicable in different situations. The weighted sum method is suitable when decision-makers can clearly quantify the weight of each objective; AHP helps decision-makers understand and evaluate each decision criterion through pairwise comparisons; while TOPSIS makes decisions based on the comparison of each scheme's distance from an ideal solution.