An Optimization Model for Building Envelope with Energy Efficiency Objectives Based on the BIM Design Buider-RF-NSGAII Algorithm

The level of energy consumption in buildings is a vital aspect related to the design and operation of a project. Choosing architectural design options and building envelope materials from the initial stages via Building Information Modeling (BIM) has emerged as a research trend aimed at reducing energy consumption in buildings. In this paper, the authors developed the optimization model, based on the BIM DesignBuilder_RF_NSGAII Algorithm, which utilizes the Random Forest machine learning algorithm to evaluate energy consumption and NSGAII to search for optimal envelope design options. Based on the results, the proposed model automatically provided Pareto optimal solutions with objectives related to cost and energy usage, determined by variables such as optimal window ratios, wall types with U-value, roof types with U-value, and glass types with Solar Heat Gain Coefficient (SHGC). The proposed multi-objective optimization model will serve as an invaluable tool for managing envelope design issues during the early project phase and achieving the highest energy efficiency in the building.