# Exploring Evolutionary Algorithms for Multi-Objective Optimization in Seismic Structural Design
## 6 Conclusions  
Energy-dissipating elements are vital for increasing the seismic resilience of structures. These elements reduce the risk of damage to structures, ensuring both life safety and minimizing economic losses. Especially in regions with high earthquake risk, the use of these dampers is increasingly being incorporated into building codes and design practices. The dissipation of seismic energy and the use of energy dissipating elements significantly improve the earthquake performance of structures. Studies in the literature have demonstrated the effectiveness and application areas of these elements in detail. While these elements make structures more resilient under dynamic loads, they also play a critical role in protecting the safety of life and property. In this study, the use of evolutionary algorithms in seismic design and reinforcement should be divided into two main categories: the design of new buildings and reinforcement of existing structures. These two areas present different challenges, goals, and constraints in terms of optimization. Since new buildings are designed in accordance with modern seismic standards, they offer a more flexible optimization process. In this process, multi-objective optimization can be achieved by considering factors such as cost, building performance, and safety. Genetic algorithms are frequently used to ensure the optimal placement of structural elements of new buildings and the most efficient use of energy-absorbing devices. These designs aim to maximize the earthquake resistance of structures, supported by the latest technologies and materials. Thanks to modern construction techniques and materials, there is a wider design freedom. The strengthening of existing structures poses a very different set of optimization problems. Most existing structures are not designed according to current seismic standards and therefore have limitations in terms of materials, geometry, and design. In the strengthening processes, factors such as the elimination of existing defects in the structure and integration of energy dissipation devices to increase the durability of the structure and cost-safety balance should be taken into consideration. In this context, evolutionary algorithms such as genetic algorithms and particle swarm optimization are used to find the most suitable strengthening solutions within the boundaries of the existing structure. Since there is a more limited range of motion during the strengthening of existing structures compared to new buildings, these algorithms operate under more constraints. Examining these two areas separately will provide a more in-depth understanding of the solutions offered by evolutionary algorithms. While the optimization of new structures offers a wider design flexibility, the strengthening of existing structures involves more constraints and complexity. Therefore, considering the optimization processes in both areas separately will more comprehensively reveal how evolutionary algorithms adapt to these different needs. Bibliometric analysis is a valuable tool for understanding the scope and evolution of research in the field of evolutionary algorithms in multi-objective optimization problems in seismic design studies. The studies mentioned above have examined different aspects of this field, revealing which topics are prominent and how research trends are evolving. Such analyses provide researchers with important guidance for future work and contribute to a better understanding of the scientific literature. In this research, we used bibliographic data from the WoS and Scopus databases to conduct a preliminary bibliometric analysis of the global literature on evolutionary algorithms in multi-objective optimization problems in the field of seismic design studies. This study is very beneficial in analyzing and providing an extensive description of how this field of study has evolved, along with identifying the principal contributors and their collaborations.