Seismic evaluation of optimal performance-based design of steel moment frames with metaheuristic algorithms

Optimal use of materials in the construction of structures is one of the main goals in any design. Because the construction of building structures is costly for their builders, therefore, structures and buildings that are economically justifiable and appropriate and meet the requirements of the criteria are more welcome. On the other hand, maintaining the performance of structures in earthquakes plays an important role in ensuring safety and reducing earthquake damage. Optimization of frames reduces sections, stiffness, and strength of components, and as a result, the performance of these frames against earthquakes has been questioned by researchers. In this research, the performance level of optimized steel moment frames with metaheuristic algorithms has been evaluated. For this purpose, the seismic performance of five-story steel moment frames with different geometric characteristics has been optimized and seismically evaluated using Particle Swarm Optimization (PSO), Charged System Search (CSS)Ant Colony Algorithm (ACO) and Genetic Algorithm (GA). The results of studies show that the optimized frame based on the Charged System Search algorithm has lower weight and lighter sections, and the seismic behavior responses of the frames are obtained faster. In terms of performance levels, the total number of collapse plastic joints in the Particle Swarm Optimization (PSO) was higher than other methods. Therefore, this algorithm can also be proposed as a suitable proposal for the optimal design of similar frames.