Application of Genetic Algorithms in Multi-Objective Optimization Design of Ultra-Low Energy Consumption Buildings with Prefabricated Steel Structures

With the rapid development of the global economy, energy and environmental issues have become a serious challenge facing the world. In the construction industry, energy conservation and emission reduction are key issues to achieve sustainable, healthy and stable development. Traditional prefabricated steel structures have many shortcomings, such as high resource consumption and long construction period. In order to solve these problems, this article proposes a new idea and achieves good results by using genetic algorithm to optimize the design of assembly-type high energy consumption targets. In order to verify the feasibility of this method, MATLAB software was used to conduct performance testing and result analysis. The results show that the average stability of the model's pre-vibration acceleration, maximum acceleration and critical speed are 0.888, 0.894 and 0.914 respectively; the average load-bearing capacity of the maximum deformation is 94.8%, and the average load-bearing capacity of the displacement change is 93.6%; the average response time of processing data is 3.4s, and the average delay time is 1.6s. This shows that the model can effectively reduce energy consumption under the optimization of genetic algorithm.