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

被引:0
作者
Huang Y. [1 ]
Zhang X. [2 ]
机构
[1] Art & Design College, Putian University, Fujian, Putian
[2] Xiamen Academy of Arts and Design, Fuzhou University, Fujian, Xiamen
关键词
Genetic Algorithm; High-rise Residential Building; Space Optimization;
D O I
10.2478/amns-2024-0750
中图分类号
学科分类号
摘要
With the rapid development of urbanization and the continuous growth of population, the design and planning of highrise 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. © 2024 Youwei Huang and Xin Zhang., published by Sciendo.
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  • [1] Broyles J.M., Shepherd M.R., Brown N.C., Design optimization of structural-acoustic spanning concrete elements in buildings, Journal of Architectural Engineering, 1, (2022)
  • [2] Danhaive R., Mueller C.T., Design subspace learning: structural design space exploration using performance-conditioned generative modeling, Automation in Construction, 127, 1, (2021)
  • [3] Ding J., Chao S., Wu H., He Z., Li J., Key technology of green building in the shanghai tower structural design, Jianzhu Jiegou Xuebao/journal of Building Structures, 38, 3, pp. 134-140, (2017)
  • [4] Frangedaki E., Sardone L., Lagaros N.D., (04021033)design optimization of tree-shaped structural systems and sustainable architecture using bamboo and earthen materials, Journal of Architectural Engineering, 4, (2021)
  • [5] Ernesto G., Maura, Imbimbo, Valentina, Tomer, (04017027)structural optimization of grid shells: design parameters and combined strategies, Journal of Architectural Engineering, 24, 1, pp. 1-9, (2018)
  • [6] Tafraout S., Bourahla N., Bourahla Y., Mebarki A., Automatic structural design of rc wall-slab buildings using a genetic algorithm with application in bim environment, Automation in construction, 106, 10, (2019)
  • [7] Ya-Nan T., Jun-Shan L., Architectural design of urban traffic hub based on regionalism and culture, Journal of Railway Engineering Society, 34, 10, pp. 78-82, (2017)
  • [8] Aleadelat W., Albatayneh O., Ksaibati K., Developing an optimization tool for selecting gravel roads maintenance strategies using a genetic algorithm, Transportation Research Record, 2674, 5, pp. 108-119, (2020)
  • [9] Molchanov V.M., Molchanova C.E., Irmanova E.V., Architectural and planning design features of high-quality housing on the «club houses» example, Materials ence Forum, 931, 2, pp. 740-744, (2018)
  • [10] Bansal V.K., (05017005)integrated cad and gis-based framework to support construction planning: case study, Journal of Architectural Engineering, 3, (2017)