Cost and CO₂ Emissions Analysis in the Multi-Objective Optimization of Steel-Concrete Composite Slabs Using the MOPSO Algorithm

Resumo

The use of steel-concrete composite slabs has expanded in recent years due to their fast construction, the elimination of formwork in most cases, and the reduction in the use of concrete and steel materials that most significantly contribute to greenhouse gas emissions in the construction industry. In this context, the present study aims to formulate a multi-objective optimization problem for steel-concrete composite slabs, focusing on minimizing CO₂ emissions and final costs, as well as increasing their load-bearing capacity. The design constraints prescribed by Brazilian standards were considered for both the construction and service stages, using the Effective Width Method (EWM), for the construction stage, and the service stage. To solve the problem, the Multi-Objective Particle Swarm Optimization (MOPSO) method was employed, and Pareto fronts were generated and analyzed based on the algorithm’s output. An equation was proposed to relate CO₂ emissions to cost. The optimization results show that MOPSO was effective in identifying optimal solutions for simply supported composite slabs using MF-75 steel decking. The manufacturer's catalog was studied to propose a new span and load table as a product of the applied multi-objective optimization, presenting composite slab solutions with identical geometric and material properties as the original ones, yet capable of supporting up to 2.64 times the design load proposed in the catalog. According to the results, the governing constraints in the optimization problem were the verification of the steel decking under bending moments before concrete curing, and the verification of the composite section under longitudinal shear after curing