Influence of parameter uncertainty on the low‐carbon design optimization of reinforced concrete continuous beams

Abstract Sustainable structural design can benefit the low‐carbon building industry. This study developed a hybrid optimization approach to analyze the influence of parameter uncertainty on the low‐carbon design optimization of reinforced concrete components. The proposed approach combined Monte Carlo simulations with a genetic algorithm for stochastic design optimization considering uncertainty in carbon emission factors. Based on a “cradle to site” system boundary that considers the production, transportation, and construction of reinforcement, concrete, and formwork, a case study of a continuous beam was conducted. The results revealed the significance of carbon emission factor choices on the optimal solutions. Further parametric analyses indicated the rational ranges of sectional dimensions and material strengths from a probabilistic perspective, and suggestions were accordingly proposed for low‐carbon design alternatives. Overall, the choices of emission factors can change the values of objective functions in the optimization, and therefore, affect the optimized design parameters of reinforced concrete beams.