Multi-objective Adaptive Guided Differential Evolution for Passively Controlled Structures Equipped with a Tunned Mass Damper

This study proposes an approach for the optimum design of tuned mass damper (TMD) in structures utilizing a multi-objective algorithm of Adaptive Guided Differential Evolution (MOAGDE). The TMD system is widely employed to mitigate structural vibrations and enhance the dynamic behavior of structures. However, the optimization of TMD-based systems often involves conflicting objectives, such as various seismic responses. To address this challenge, we present the MOAGDE approach that simultaneously optimizes the TMD parameters to achieve the desired balance between different objectives. The proposed algorithm employs a combination of metaheuristic method of Adaptive Guided Differential Evolution (AGDE) and Pareto dominance principles to explore the trade-off between the structural response objectives. By iteratively updating solutions and selecting promising ones based on Pareto dominance, the algorithm efficiently searches for a set of optimum solutions that offer a range of design options with different trade-offs between structural acceleration and displacement objectives. To assess the efficiency of the proposed method, a case study on a representative TMD-based controlled structure is investigated. The results demonstrate that the MOAGDE can effectively identify a set of Pareto optimum solutions. This provides designers with a tool to make wise decisions during the design process, enabling the selection of TMD parameters that best meet the specific requirements of a given structure.