Sustainability in Prefabricated Construction: Enhancing Multicriteria Analysis and Prediction Using Machine Learning

Abstract

Multicriteria analysis is widely used to prove the excellence of prefabricated construction compared with conventional construction. However, because previous studies have not presented the results of an integrated analysis, identifying the merits of prefabricated construction is challenging. Furthermore, clients experience difficulty when considering prefabricated construction owing to the complexity of simulations and the lack of data. Therefore, this study aimed to conduct a multicriteria analysis for prefabricated construction considering productivity, safety, environment, and economy, and develop a multi-prediction model. This study was conducted in five stages. Results revealed that prefabricated construction was superior to conventional construction for all variables, with the former scoring 0.0927 on average and the latter scoring 1.863. The multiprediction model utilizing a decision tree and Bayesian optimization has a high performance, achieving over 94%. Using study findings, decision makers can use the multiprediction model to assess the expected performance of prefabricated construction. This enables a comprehensive comparison of various conditions across different aspects through the multicriteria analysis.