Research on Space Optimization Design of High-rise Residential Building Based on Genetic Algorithm

Abstract

Abstract With the rapid development of urbanization and the continuous growth of population, the design and planning of high-rise residential buildings have become increasingly important. The purpose of this study is to explore the space optimization design method of high-rise residential buildings based on genetic algorithm(GA), focusing on the comparative analysis between traditional GA and Adaptive genetic algorithm(AGA). In this paper, AGA is used to establish the spatial optimization model of high-rise residential buildings. By dynamically adjusting the parameters of the algorithm, AGA makes the algorithm better adapt to the characteristics of the problem and improves the search efficiency. The results show that AGA is superior to traditional GA in global convergence probability, especially when the population size is large. AGA improves the adaptability and robustness of the algorithm by dynamically adjusting the crossover and mutation probability. AGA has better flexibility and adaptability in the design of high-rise residential buildings and is expected to provide more optimized solutions for solving complex design problems. The findings of this study provide a useful reference for innovation and sustainable development in the field of high-rise building design and also provide practical methods and tools for the application of GA.