A Multiobjective Optimization Algorithm for Building Interior Design and Spatial Structure Optimization

Abstract

Based on the global big data environment, people have more and more requirements for the interior design and spatial structure of buildings, and the traditional design has been unable to meet people’s needs, and the importance of artificial intelligence decision-making is reasonably reflected in the process of building interior design and space structure optimization. There are a variety of algorithms for artificial intelligence decision-making, artificial neural networks, and correlation coefficient analysis methods, and expandable interior design mining methods are currently being continuously improved and evolved, and these algorithms are used to analyze each case and then screen and finally obtain the optimal results, and the proposed multiobjective optimization and constraint optimization make the research work provide a new strategy for the design development of the data age. In the case of the Library of Extremely Cold Lands, the solution set quality of the nonadaptive solution is verified, the convergence, uniformity, and extensiveness are optimized, and then the experimental process is analyzed, and finally the multiobjective conclusion that building interior design and spatial structure still needs to be further optimized for artificial intelligence decision-making is obtained.