shape optimization of arch dams with frequency constraints by enhanced charged system search algorithm and neural network

the main aim of this paper is to find the optimum shape of arch dams subjected to multiple natural frequency constraints by using an efficient methodology. the optimization is carried out by charged system search algorithm and its enhanced version. computing the natural frequencies by finite element analysis (fea) during the optimization process is time consuming. in order to reduce the computational burden, back propagation (bp) neural network is trained and utilized to predict the arch dam natural frequencies. it is demonstrated that the optimum design obtained by the enhanced charged system search using the bp network is the best compared with the results of other algorithms. the numerical results show the computational advantageous of the proposed methodology.