Multi-objective optimization of prestressed composite steel and concrete beam via multi-objective particle swarm optimization

With the global increase in greenhouse gas emissions, the need for economically and environmentally friendly solutions in the construction industry has never been more urgent. This study aims to propose a multi-objective optimization problem formulation for prestressed composite steel and concrete beams. The objective functions considered are the minimization of the final cost and CO2 emissions from the materials used in their fabrication and the maximization of the live load capacity that the beam can support. Constraints include the requirements for composite steel and concrete elements according to Brazilian standards. The Multi-objective Particle Swarm Optimization (MOPSO) algorithm was implemented to solve the optimization problem and generate the Pareto fronts. Examples demonstrating the solution's effectiveness were compared with examples from the literature. The Pareto fronts show that different solutions can be found for the same load; the best results were obtained when using concrete with a compressive strength exceeding 45 MPa, reaching a maximum value of 50 MPa. Steel is the primary material contributing to both cost and CO2 emissions, while concrete is the second-largest contributor to final CO2 emissions. According to the results, searching for materials with greater resistance and low environmental impact is still necessary.