Research on Optimization of Architectural Heritage Based on Artificial Intelligence

Modern and contemporary architectural heritage possesses unique architectural value, yet often suffers from poor thermal comfort and high energy consumption. Their preservation and reuse require a synergistic optimization of value preservation with other environmental, social, and economic performance aspects. The multi-objective optimization renovation decision-making system for modern heritage buildings, based on intelligent algorithms, distinguishes itself from previous experience-based approaches to building heritage reuse by conducting targeted quantitative analysis of the object to be renovated. This system clearly defines the goals and analyzes the benefits of renovation measures on those goals, ensuring that renovations are conducted within the framework of policies and protection regulations while anticipating their benefits. Incorporating multi-objective optimization algorithms into the multi-objective optimization renovation decision-making system for modern heritage building reuse holds significant importance. This approach adopts a “from engineering to theory and back to engineering” methodology, where targeted analysis of the heritage building is conducted, followed by selection of appropriate renovation points and critical thermal parameters. Utilizing intelligent algorithms, optimization is performed to select parameters that meet the defined objectives, and specific renovation measures are determined based on these parameter selections.