Parameter-Free Metaheuristic-Based Method for Reinforced Concrete Frame Cost Optimization

This study proposes a parameter-free metaheuristic optimization framework using the Jaya and Rao algorithms for the cost-based design of reinforced concrete (RC) frames in accordance with ACI 318-25. Beam and column dimensions are treated as design variables within predefined bounds, and the objective was to minimize the total construction cost including concrete and reinforcing steel. Structural analysis was performed using the matrix displacement method. The performance of the Jaya, Rao-1, Rao-2, and Rao-3 algorithms was evaluated through multiple independent runs. All methods achieved optimal or near-optimal solutions; however, Rao-2 demonstrated competitive performance with low mean values and favorable statistical performance. The results confirm the effectiveness of parameter-free metaheuristic methods for RC structural cost optimization. Unlike previous studies, this study explicitly focuses on parameter-free metaheuristic algorithms and evaluates their robustness through statistical analysis on reinforced concrete frame systems. The main contribution lies in demonstrating the comparative performance and practical applicability of parameter-free algorithms without the need for algorithm-specific parameter tuning.