computer-aided hard-structural optimization problems using discrete special relativity search algorithm

Optimizing tall structures is essential for reducing material use and construction costs, yet complex geometries, nonlinear responses, and dynamic load requirements make the process challenging. this study applies an improved discrete special relativity search (dsrs) algorithm to optimize a 50-story, 150-meter steel high-rise with irregular geometry under seismic, wind, gravity, and thermal loads. dsrs handles discrete design variables representing structural sections, aiming to minimize total structural weight while satisfying stringent design constraints, including seismic drift, panel zone shear, and strong column–weak beam criteria. results after 3000 function evaluations show that dsrs achieves a substantially lower structural weight compared to ant colony optimization (aco), while fully satisfying all design constraints. the method delivers rapid convergence, consistent performance, and efficient material usage. findings demonstrate dsrs's capability to solve large-scale, discrete, and constraint-heavy engineering problems, offering a robust and practical approach for high-rise structural optimization in demanding seismic and wind conditions.