An open-source GA framework for optimizing the seismic upgrading design of RC frames through BRBs

Optimizing seismic upgrading interventions in reinforced concrete (RC) structures is a difficult task, due to the inner non-linearity of the analyses usually performed. Additionally, it is well known that the displacement demand to the structure depends from the mass and stiffness of the system, and consequently its definition cannot be made a-priori. This paper presents the application of a soft-computing method -i.e. Genetic Algorithm (GA)- for the shaping optimization of code-compliant seismic upgrading interventions on plane RC frames through Buckling-Restrained Braces (BRB). The metaheuristic procedure allows to minimize the cost while ensuring the required safety level, without the need of evaluating all the possible solutions. The main GA operators (selection, crossover and mutation) contribute to explore the research space and evolve the suitable results toward the optimal one. The procedure is developed in an entirely open-source environment, taking advantage of Python for implementing the GA and OpenSeesPy for the structural analysis. The results of the procedure are compared with the outcomes of Monte Carlo simulations, showing the stability and the efficacy of the proposed algorithm.