An Innovative Tool for Weight Reduction in Architecturally Constrained Steel Buildings using Enhanced Genetic Algorithm - Fathi, Mohamed Mahmoud; Hamdy, Tarek Fouad; Gomaa, Mohamed Sayed (Engineering, Technology & Applied Science Research, 2025)
This study integrates theoretical optimization with practical structural design by introducing an innovative tool that combines SAP2000 and Genetic Algorithm (GA) to optimize bracing configurations while ensuring compliance with safety standards and architectural constraints. The proposed tool provides a fast, automated, and cost-efficient alternative to conventional design approaches by incorporating an enhanced GA procedure that significantly reduces computation time. A two-step validation confirms its accuracy by comparing the results with existing research and benchmarking against the trial-and-error method. Through four case studies, including symmetrical and asymmetrical layouts with regular and irregular column spacing, the introduced tool achieved up to 65.16% weight reduction while analyzing only up to 2.1% of the total solution space compared to trial-and-error procedures. The findings demonstrate the tool’s effectiveness in minimizing structural weight while meeting seismic design requirements, offering valuable insights for implementing optimized and cost-efficient design solutions in modern architecture.