@article{bibcite_15913,
  author = {Zhen-Song Chen and Kou-Dan Chen and Ya-Qiang Xu and Witold Pedrycz and Miros{\l}aw Skibniewski},
  title = {Multiobjective optimization-based decision support for building digital twin maturity measurement},
  abstract = {<p>The\&nbsp;<a href="https://www.sciencedirect.com/topics/computer-science/digital-twin" title="Learn more about digital twin from ScienceDirect{\textquoteright}s AI-generated Topic Pages">digital twin</a>\&nbsp;(DT) represents a powerful tool for advancing construction industry to provide a cyber{\textendash}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\&nbsp;<a href="https://www.sciencedirect.com/topics/engineering/multiobjective-optimization" title="Learn more about multiobjective optimization from ScienceDirect{\textquoteright}s AI-generated Topic Pages">multiobjective optimization</a>\&nbsp;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.</p>
},
  year = {2024},
  journal = {Advanced Engineering Informatics},
  volume = {59},
  month = {01/2024},
  doi = {DOI: 10.1016/j.aei.2023.102245},
  language = {eng},
}