Decision-making (DM) at the early building design stages is essential to optimise sustainability performances. Nevertheless, the current methods of optimising building sustainability are complex as they involve multiple design variables and performance objectives. With the development of building information modelling (BIM), complicated buildings can be digitally constructed with precise geometry and accurate information for design optimisation in the early stages of project. Thus, this study explores the use of BIM and Genetic Algorithm (GA) to support DM and optimisation for sustainable building envelope design. To develop a BIM-GA optimisation method, Autodesk Revit template was created to extract data of building envelope from a Base Model (BM). Then, the data were employed to compute overall thermal transfer value (OTTV) and construction cost for BM evaluation and GA optimisation. A hypothetical building was modelled and then analysed using the proposed method as a test case. The BIM-GA optimisation method can address the difficulties of DM on building sustainability in the early design process.

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Green retrofit is crucial to turning existing buildings into green buildings, but its design and analysis process is dependent on numerous disjointed methods. Various decisions are required to optimise the building efficiency, such as the choices of building materials, opening sizes, and glazing types. Therefore, this study explores the application of computational building information modelling (BIM) to automate the process of design decision-making for green retrofitting of the existing building envelope. A BIM tool (Revit), a visual programming tool (Dynamo) and multi-objective optimisation algorithm were integrated to create a computational BIM-based method for building envelope retrofitting by optimising overall thermal transfer value (OTTV) and construction investment cost. The proposed model was validated through a case study; the results showed that the optimised design achieved 44.78% reduction in OTTV with investment costs of RM (Malaysian ringgit) 369,182. The newly formulated computational BIM-based approach can improve the level of automation in green retrofitting design decision-making.

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