Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design

Abstract

In order to achieve the rationality and economy of shear wall layout, an improved algorithm was designed in the architectural design program. The improved algorithm is based on the basic framework of genetic algorithm and particle swarm optimization algorithm, first adjusting the inertia weight, and then introducing elimination mechanism and mutation rate control. A shear wall design model was constructed using an improved algorithm, which was applied to determine the layout of shear walls in a 28 story high-rise building in a certain city. The example results show that when using the designed shear wall design program for scheme design, the success rate reaches 100 %, which is 38.47 % higher than the original particle swarm optimization algorithm. The obtained optimization scheme has interlayer displacement angles of 1/2096 and 1/1800 in the vertical and horizontal directions, respectively, while the torsional displacement ratio in both directions is 1.0908 and the torsional period ratio is 0.7125. After optimizing the algorithm, the length of the shear wall material was saved by 10.97 %, effectively reducing the use of materials. This not only reduces construction costs, but also brings higher space utilization efficiency. The building design scheme obtained from this study not only meets national standards, but also has lower computational time costs. This study demonstrates the potential application of this design algorithm in solving traditional architectural design problems. This not only provides new tools for the field of architectural design, but also stimulates more interdisciplinary cooperation, integrating computer science, artificial intelligence technology more closely with building engineering.