Optimization of recycled aggregate concrete mix ratio based on multi-objective optimization algorithm

Abstract In response to the poor chloride ion penetration resistance and economic viability of Recycled Aggregate Concrete (RAC), this study first analyzes the main influencing factors of the chloride ion penetration resistance of RAC and constructs a support vector regression benchmark prediction model. The particle swarm optimization is taken to establish a coupling prediction model. Finally, based on the economic cost of materials, a multi-objective optimization algorithm is built to improve the mix ratio of RAC. Compared with the comparison model, the coefficient of determination of the measured and predicted values of the constructed coupled model was 0.9842 and 0.9736, respectively, and the average absolute errors were 0.1923 and 0.7225, respectively. Meanwhile, after optimizing the designed method, the chloride ion diffusion coefficient and economic cost of each group of RAC were significantly reduced, with reduction rates exceeding 9% and 2%. The mix ratio optimization method is effective. This method significantly enhances the chloride ion penetration resistance of RAC and effectively improves its durability. It also significantly reduces the economic cost, laying a solid foundation for the widespread application of RAC and effectively promoting RAC in engineering construction.