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Showing 3 results for Enhanced Charged System Search

A. Kaveh, M. Nikaeen,
Volume 11, Issue 3 (9-2013)
Abstract

In this research, the Charged System Search (CSS) and Enhanced Charged System Search (ECSS) algorithm are used to obtain the optimum design of irregular grillage systems with different spacing and various boundary conditions. The cross-sectional properties of the beams are selected as the design variables and the weight of structure is used as the objective function. The displacement limitations and permissible stress constraints are employed from LRFD-AISC and are considered in the formulation of the design problem. Furthermore, in obtaining the response of the grillage systems, the effect of warping is also taken into account. The comparison of the results shows that warping changes the beam spacing, and different boundary conditions have substantial effects on the optimum design of irregular grillage systems
A. Kaveh, H. Safari,
Volume 12, Issue 3 (9-2014)
Abstract

The paper presents a hybrid-enhanced algorithm based on CSS for discrete problems whit the focus on traveling salesman problem. The CSS algorithm based on some principles from physics and mechanics, utilize the governing Coulomb law from electrostatics and Newtonian laws of mechanics. However, the CSS is more suitable for continuous problems compared with discrete problems. In this paper, we have tried to resolve this defect of CSS algorithm with the help of local search methods and nearest neighbor for discrete problems whit the focus on traveling salesman problem (TSP). To prove the efficiency of the proposed algorithm, results compared with the results of benchmark problems. Then, the proposed algorithm is used to solve the TSP, using as a method for solving the single row facility layout problem (SRFLP). To prove the efficiency, the results are compared with the results of benchmark problems reported in the recent literatures.
A. Kaveh, R. Ghaffarian,
Volume 13, Issue 1 (3-2015)
Abstract

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.

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