A modified real-coded genetic algorithm to identify the parameters of large structural systems subject to the dynamic loads is presented in this article. The proposed algorithm utilizes several subpopulations and a migration operator with a ring topology is periodically performed to allow the interaction between them. For each subpopulation, a specialized medley of recent genetic operators (crossover and mutation) has been adopted and is briefly discussed. The final algorithm includes a novel operator based on the auto-adaptive asexual reproduction of the best individual in the current subpopulation. This latter is introduced to avoid a long stagnation at the start of the evolutionary process due to insufficient exploration as well as to attempt an improved local exploration around the current best solution at the end of the search. Moreover, a search space reduction technique is performed to improve, both convergence speed and final accuracy, allowing a genetic-based search within a reduced region of the initial feasible domain. This numerical technique has been used to identify two shear-type mechanical systems with 10 and 30 degrees-of-freedom, assuming as unknown parameters the mass, the stiffness, and the damping coefficients. The identification will be conducted starting from some noisy acceleration signals to verify, both the computational effectiveness and the accuracy of the proposed optimizer in presence of high noise-to-signal ratio. A critical and detailed analysis of the results is presented to investigate the inner work of the optimizer. Finally, its performances are examined and compared to the most recent results documented in the current literature to demonstrate the numerical competitiveness of the proposed strategy

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This paper deals with the optimum design of vibration absorbers utilized to reduce undesirable vibrational effects which are originated in linear structures by seismic excitations. The single linear tuned mass dampers problem is treated and it is assumed that earthquake can be represented by a stationary filtered stochastic process. In the present problem, the objective is to minimize the maximum of the dimensionless peak of displacement of the protected system with respect to the unprotected one. Moreover, the constrained optimization problem is also analysed, in which a limitation of tuned probability of failure is imposed, where failure is related to threshold crossing probability by the maximum displacement over an admissible value. Examples are given to illustrate the efficiency of the proposed method. The variation of the optimum solution versus structural and input characteristics is analysed for the unconstrained and constrained optimization problems. A sensitivity analysis is carried out, and results are presented useful for the first design of the vibrations control strategy.