Multi-objective comprehensive optimization of existing building transformation based on genetic algorithm and variation calculation

In recent years, resources, energy consumption and greenhouse gas emissions generated by construction activities have attracted worldwide attention, and energy conservation and emission reduction have become the main goal of the development of the construction industry. In China, green buildings have been carried out in a large number of new buildings and achieved good results, but the existing buildings have problems such as large inventory, aging envelope structure, outdated system equipment and so on, resulting in high energy consumption and carbon emissions. On this basis, this paper USES the dominant elite traversal and mutation of genetic algorithm to calculate, according to “Environmental priority-Carbon emission and comfort optimization-Price-performance balance” series of typical model of multi-objective comprehensive optimization logic implementation, explore in comfort and carbon emission reduction targets under the optimal combination of the strategy, supplemented by the incremental cost factors, To determine the optimal solution of performance-oriented reconstruction, so as to achieve an effective and efficient ratio of design, resources and finance, which has a reference significance for the improvement of cost-performance of large-scale existing building reconstruction in China.