Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.
The problems of lateral displacement control and usability of a structure are treated as the main part in high-rise buildings. Lateral displacement and usability control can be effectively managed through stiffness design. In this paper the non-dominated sorted genetic algorithm, NSGA-II, which may be used to satisfy many objective functions is applied to the structural design of high-rise buildings. However, the rate of convergence is slower because the number of structural analysis and the amount of calculation increases. The resizing technique is efficient for displacement control because of the redistribution within the structure. An important objective is to improve the convergence speed by using the optimal design technique because the algorithm finds an optimal solution without sensitivity analysis and complex calculations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.