Multi-Objective Comparative Analysis of High-Strength Steel–Concrete Composite Columns

Steel–concrete composite tubular columns have become increasingly attractive for sustainable structural applications due to their high load-carrying capacity and efficient material utilization. However, optimizing their structural performance while simultaneously minimizing embodied carbon emissions and material cost remains a challenging multi-objective problem. This study presents a comprehensive optimization framework for circular, rectangular, and square composite tubular columns composed of high-strength materials, and using the Particle Swarm Optimization (PSO) and Multi-Objective Particle Swarm Optimization (MOPSO) algorithms. The multi-objective optimization simultaneously maximizes axial load capacity while minimizing embodied CO2 emissions, considering both sections with (WR) and without (WoR) additional longitudinal reinforcement, enabling the identification of optimal trade-offs between structural performance and environmental impact. Design variables include the cross-sectional dimensions, concrete compressive strength, steel yield strength, and reinforcement configuration. The resulting Pareto-optimal solutions are further evaluated using a multi-criteria decision-making approach based on Minkowski Metrics combined with Entropy Theory to identify the best overall compromise solution. The numerical results demonstrate that the use of high-strength materials can reduce embodied CO2 emissions by up to 16% in the analyzed cases. The implemented load-bearing capacity formulation was also validated against experimental results, yielding a mean Nexp/NNBR16239 ratio of 1.01 for the six specimens analyzed. The multi-objective formulation associated with Minkowski metrics produces a robust tool for determining the best solutions in general, as well as the best solutions related to the maximum load that the columns can support. Finally, for both the single-objective and multi-objective problem analyses, increasing the slenderness of the columns resulted in more costly solutions, both economically and environmentally.