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As a main carrier mode for the sustainable development of the construction industry in China, prefabricated building may lead to problems such as cost overruns, project delays, and waste of resources due to unreasonable selection of prefabricated components. Therefore, we quantitatively analyze the contribution rate of quality optimization of prefabricated components using QFD-SEM. Under the constraints of prefabrication rate, quality optimization contribution rate, and expected values of various sub-goals, we propose a multi-objective optimization method for prefabricated component combinations based on cost, duration, and carbon emissions. By using NSGA-II to solve the model, we can obtain a set of optimal Pareto solutions for prefabricated component combinations. Based on the optimal Pareto solution set, we establish a multi-objective evaluation model using simulated annealing optimization projection tracing method, and select the optimal prefabricated component combination solution according to the projected eigenvalues of the solutions. An empirical study is conducted using an eleven-story framed building in Shenzhen, Guangdong Province, China as a case study. The results show that: (1) Using this method, optimal solutions can be obtained in an unbounded solution space, with the optimal solution having advantages over both fully cast-in-place and fully prefabricated solutions. Compared to the fully cast-in-place solution, the duration and carbon emissions are reduced by 36.62% and 12.74% respectively, while compared to the fully prefabricated solution, costs are reduced by 4.15%. (2) There is a certain negative correlation between the cost of prefabricated component combinations and duration, carbon emissions, and quality optimization, while there is a certain positive correlation with the prefabrication rate. (3) The size of the optimal projection direction vector based on the optimization objectives indicates that carbon emissions have the greatest impact on the evaluation results of the solutions. [ABSTRACT FROM AUTHOR]

As an important part of the prefabricated building standard system, the evaluation standards for prefabricated buildings play an important guiding role in the construction and development of prefabricated buildings. However, at present, the national evaluation standards for prefabricated buildings are highly extensive and general, and some of their contents are not well considered, while local standards based on the national standard have been formulated in accordance with the actual situation in their respective regions, which makes the evaluation of prefabricated buildings in various regions more confusing, which also causes differences when calculating the prefabrication rate, restricting the development of prefabricated buildings. In order to promote the construction of a complete evaluation standard system for prefabricated buildings in China, this paper combs through the methods used for the calculation of the prefabrication rate of prefabricated buildings in 28 provincial-level administrative regions in China, conducts a comparative analysis and empirical research on the calculation of the prefabrication rate under different standards in four dimensions, and applies t-tests and simulated annealing algorithms to optimize the projection pursuit model to analyze the differences in the total scores of the prefabrication rate under different standards, as well as the key factors that affect them. The study shows that (1) the same building may have different prefabrication rates under different standards for prefabricated buildings, and the way of calculating the prefabrication rate and the scoring criteria of the evaluation items will result in significant differences in the calculated prefabrication rate. (2) Depending on the value of the optimal projection direction vector, it was found that among the evaluation criteria, the enclosure wall and the internal partition wall have the greatest influence on the total score value, while the main structure has the least influence on the total score value. (3) There are similarities as well as differences in the evaluation criteria of prefabricated buildings in each province. On this basis, by analyzing the reasons for these differences, corresponding suggestions are made for governments needing to formulate or revise local standards. [ABSTRACT FROM AUTHOR]