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In this study, application of operational modal analysis and bees algorithm (BA) in order to finite model updating (FE) are investigated. BA optimization algorithm applies Instinctive behavior of honeybees for finding food sources. An objective function is defined as the sum of the squared error between obtained natural frequencies by operational modal analysis and finite element method. Experimental natural frequencies are determined by stochastic subspace identification (SSI) which is considered as one of the strong methods of operational modal analysis. In order to investigation the accuracy of this method, BA and SSI methods are implemented on a three story structure to update parameters of its finite element model. Furthermore, to study of effectiveness of BA algorithm, the results of BA algorithm are compared with particle swarm optimization algorithm and Nelder-Mead algorithm. The results show that BA optimization algorithm, in comparison with the other optimization methods, is more accurate and simpler to update finite element model