Generation of semantically rich as-built Building Information Models (BIMs): A derivative-free optimization approach
Grant Data
Project Title
Generation of semantically rich as-built Building Information Models (BIMs): A derivative-free optimization approach
Principal Investigator
Dr Xue, Fan
(Principal Investigator (PI))
Co-Investigator(s)
Professor Lu Weisheng Wilson
(Co-Investigator)
Duration
42
Start Date
2018-01-01
Amount
454157
Conference Title
Generation of semantically rich as-built Building Information Models (BIMs): A derivative-free optimization approach
Presentation Title
Keywords
as-built BIM, building information modeling, derivative-free optimization, optimization-based modeling, semantic BIM component dataset
Discipline
Building and Construction,Operations Research
Panel
Engineering (E)
HKU Project Code
17201717
Grant Type
General Research Fund (GRF)
Funding Year
2017
Status
Completed
Objectives
1) To develop a general transformation to model as-built BIM generation as a nonlinear optimization problem of fitting BIM components; 2) To establish a semantic BIM component dataset to integrate open access BIM resources in various formats from various sources; 3) To adopt and fine-tune state-of-the-art DFO algorithms for solving the nonlinear optimization problem to generate semantically rich as-built BIMs.