02077nas a2200169 4500000000100000000000100001008004100002260001200043100001900055700001700074700001600091700001900107700002600126245010200152490000700254520164600261 2024 d c01/20241 aZhen-Song Chen1 aKou-Dan Chen1 aYa-Qiang Xu1 aWitold Pedrycz1 aMirosław Skibniewski00aMultiobjective optimization-based decision support for building digital twin maturity measurement0 v593 a

The digital twin (DT) represents a powerful tool for advancing construction industry to provide a cyber–physical integration that enables real-time monitoring of assets and activities and facilitates decision-making. Due to the inherent characteristics of the construction industry and the diverse possibilities with DT, proliferation of building digital twin (BDT) necessitates a comprehensive comprehension of its evolution and the creation of roadmaps. This paper aims to contribute to the formalization and standardization of BDT. It designs a novel assessment framework for the overall maturity measurement of existing BDT projects. The developed BDT maturity model incorporates a collective opinion generation paradigm based on a fairness-aware multiobjective optimization model to provide an expert-based evaluation system for evaluating the maturity of BDT projects. The effectiveness and feasibility of the proposed framework have been validated through a case study of an experimental BDT initiative. This paper establishes a generalizable framework for BDT maturity assessment that can offer insights into BDT maturity standards to construction practitioners to create effective strategies for the diffusion, development, and maturation of BDT.