A category of methods developed in the branch of artificial intelligence known as genetic algorithms is suggested for numerical estimation and experimental design of dynamic tuning and resonance limit state analysis in ultimate dynamic states of structures in civil engineering. The performance of a set of genetic algorithms is presented by using the application problems. The results indicate that genetic algorithms are promising tools for solving nonlinear optimization problems, even when the objective function is either discrete, nonconvex, mulitmodal or flat in shape. The applications are performed on the adoption of up-to-date vectorized numerical methods for wave propagation and ultimate transient dynamics problems and optoelectronical experimental approaches for resonance tuning of engineering structures and technologies submitted to limit state dynamic loads.
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