Evaluation of Thermal Insulation Performance of Building Exterior Wall Based on Multiobjective Optimization Algorithm

A complete evaluation of conflicting and nonlinear multiperformance is referred to as an evaluation system. Therefore, multiobjective optimization research for building performance is of great importance. Considering the above problems, this paper proposes a multiobjective performance optimization platform at the architectural design stage. The optimization research is combined with the basic algorithms. It is based on Grasshopper software. It aims to provide a fast and effective method for the optimization design of sustainable buildings. It is important to note that this workflow has no restrictions on what to optimize for or what to target, and can be determined on a case-by-case basis. To evaluate the use of the work platform and make the research results more extensive, the standard model of the inner corridor space building in office buildings in cold areas was extracted. The extracted standard model was taken as the final research object. At the same time, the convergence, distribution, and comprehensive evaluation indexes of the simulation results were analyzed. The quantitative influence parameter system of window parameters on the total building energy consumption, lighting uniformity, and glare probability was established. A series of parametric design models based on the comprehensive optimal solution of building energy consumption and lighting quality was obtained. The main purpose of this paper is to design a green building design method based on the principle of goal-oriented design. This paper, combined with the group search function of nondominated genetic algorithm (NSGA-II), the energy consumption of the building, and the evaluation function of indoor thermal and humid environment, is obtained and linked with MATLAB. The energy consumption of residential buildings and indoor thermal comfort were taken as the optimization objectives of the design scheme. The automatic optimization model of the architectural design scheme was established. Finally, the Pareto solution set of the architectural design scheme is obtained, and the designer can select the appropriate design scheme of the Pareto solution set according to the actual situation of the project, to meet the requirements of green building design. The design scheme optimized by this method can effectively reduce building energy consumption and improve indoor thermal comfort.