## 2 State of the Art
### Reliability Analysis
The integration of Multi-Objective GAs (MOGAs) and FE is used in this study, together with OpenSees 3.7.0 software, which is dedicated to detailed reliability assessments under random wind loading for the development of the tower's topology and geometric and member sizes. The methodology also bears the advantage of using the importance sampling technique to cut down computer time and focus on sensitive random variables. The findings of the study indicate that the proposed methodology identifies the relationship between the conflicting objectives, the reliability index, and the overall weight, thus equipping the design engineers with the information that can enable informed decisions. The efficient implementation of Optimization with Nonlinear Structural Reliability Analysis is presented in another article [57] by employing OpenSees. This method enhances the reliability and performance of the structural designs by incorporating variability of such values as design parameters and structural parameters by employing the FORM. The results demonstrate several numerical examples of how optimization can be effective in real-life structures such as trusses and frames. The referenced study [7] appears as another example that uses GAs in conjunction with Nonlinear FE Reliability Analysis using OpenSees to analyze RBDO. The paper shows that, using GAs along with FE analysis, one can solve real-world optimization problems that are nonlinear and probabilistic. This makes it possible to design structures that satisfy the reliability requirements under uncertain loads such as wind, earthquake, and wave loads. Another manuscript [58] presents a strategy incorporating a Complex-Step Approximation (CSA) option with the FORM for sensitivity analysis and RBDO. For more information on the structural and system reliability analysis with a theoretical background and real-world examples, readers can refer to the referenced book [59]. Briefly, RBDO methods are mostly general and can suit any problem; they do not often depend on the deterministic information of the functions, such as derivatives, included in the formulation of the problem, but can also deal with definite design variables [9]. As can be observed, the examined literature examples mostly employ textual programming or software rather than specialized AEC applications. Due to these reasons, the present study utilizes VP, parametric modelling, and the FORM in the BIM environment to perform RBDO, accelerating its adoption and enabling the widespread application of established methodologies from the rich literature in design workflows. This significance of the present study has been, moreover, enhanced by validating the proposed methodology with real-world examples and providing and comparing RBDO optimized models with structurally optimized models, along with employing different MA. Moreover, visualization and validation with MCS and RSA models provide seamless integration and reliability towards the study's significance. Lastly, all codes are open-source and can be found on a specifically created GitHub account [60], which provides a valuable chance for the reproducibility and enhancement of the proposed methodology.