Towards sustainable reinforced concrete beams: multi-objective optimization for cost, CO2emission, and crack prevention

The growing scarcity of natural resources drives the construction sector to seek solutions where materials are employed not only for greater cost-effectiveness but also for improved performance and increased sustainability. This study aimed to use optimization in the design of reinforced concrete beams, aiming to reduce costs, CO2emissions, and concrete cracks. Considering the conflicting nature of the objectives, a multi-objective optimization was performed using the Non-dominated Sorting Genetic Algorithm (NSGA-II). The design variables considered were the dimensions of the cross-sectional area and the number of steel bars in the bottom layer of the beam. Beams with varying spans and concrete strengths were optimized, and Pareto frontiers were obtained. The results allowed for the identification of the most relevant parameters for each objective considered, as well as the behavior of each variable in obtaining the optimized solutions. Among the main conclusions, it was found that the least costly solutions also correspond to the lowest impact and that greater width can be advantageous in increasing the durability of the beams.