Design optimization of public building envelope based on multi-objective quantum genetic algorithm

The sustainable development of buildings addresses climate change which can be achieved by the envelope design. However, when optimizing design schemes for building energy conservation, the impact of embodied carbon emissions from building materials is often overlooked. Establishing a rapid and effective optimization model to balance diverse objectives holds significant research importance in this context. Therefore, this paper aims to develop an optimal decision support model for envelope materials. The genetic algorithm is commonly utilized in optimizing building design. However, it has the drawback of being prone to local optima. In response, the paper proposes an approach for envelope design optimization based on the Multi -Objective Quantum Genetic Algorithm (MOQGA). Finally, the model and algorithm are validated through a case study conducted on a public building in Yantai, evaluating the obtained Pareto front to demonstrate the trade-offs among objectives. The findings indicate that the model effectively decreases energy consumption, carbon emissions, and investment costs during the building design phase. Comparative analysis with NSGA-II demonstrates the strong search and optimization capabilities of the proposed method. This research provides quantitative references for public building designers to coordinate environmental, economic, and energy efficiency optimization during the design phase.