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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.

Studying how various economic activities affect the environment is becoming increasingly important, especially in light of the greenhouse effect's contributing factor, atmospheric carbon dioxide (CO2) emissions. With all the extraction, production, and transportation of materials involved in its supply chain, civil building is one of the economic activities with the biggest environmental impact. Concrete, one of the most used building materials, stands out for significantly increasing CO2emissions. In order to lessen the environmental impact of reinforced concrete building structures, this work evaluates the CO2emissions of materials, as well as the variations in those emissions caused by the used databases. Initially, three scenarios that took into account various characteristic strengths and the cradle-to-gate phase were considered to analyze CO2emissions from the raw materials used in the manufacturing of reinforced concrete for the same research region. These scenarios were obtained considering: a survey of emissions from the main raw materials involved in the production and execution of reinforced concrete structures in the region of study; the use of global emissions obtained with SimaPro software; and the adaptation, in the same software, to values obtained to the study region, related to concrete mixes, transportation distances, and electricity consumption. In the sequence, a reinforced concrete building structure was analyzed considering the adopted scenarios, and the behaviors and contributions of elements and components were investigated. Among the conclusions, the study demonstrated the importance of using local data collected particularly for the study region rather than data from global databases. In addition, it was found that the most environmentally beneficial concrete, considering the whole building, corresponded to those with lower characteristic strengths.