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        Design of steel frames by an enhanced moth-flame optimization algorithm

        Saeed Gholizadeh,Hamed Davoudi,Fayegh Fattahi 국제구조공학회 2017 Steel and Composite Structures, An International J Vol.24 No.1

        Structural optimization is one of the popular and active research areas in the field of structural engineering. In the present study, the newly developed moth-flame optimization (MFO) algorithm and its enhanced version termed as enhanced moth-flame optimization (EMFO) are employed to implement the optimization process of planar and 3D steel frame structures with discrete design variables. The main inspiration of this optimizer is the navigation method of moths in nature called transverse orientation. A number of benchmark steel frame optimization problems are solved by the MFO and EMFO algorithms and the results are compared with those of other meta-heuristics. The obtained numerical results indicate that the proposed EMFO algorithm possesses better computational performance compared with other existing meta-heuristics.

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        Optimal design of double layer barrel vaults considering nonlinear behavior

        Saeed Gholizadeh,Changiz Gheyratmand,Hamed Davoudi 국제구조공학회 2016 Structural Engineering and Mechanics, An Int'l Jou Vol.58 No.6

        The present paper focuses on size optimization of double layer barrel vaults considering nonlinear behavior. In order to tackle the optimization problem an improved colliding bodies optimization (ICBO) algorithm is proposed. The important task that should be achieved before optimization of structural systems is to determine the best form having the least cost. In this study, an attempt is done to find the best form then it is optimized considering linear and non-linear behaviors. In the optimization process based on nonlinear behavior, the geometrical and material nonlinearity effects are included. A large-scale double layer barrel vault is presented as the numerical example of this study and the obtained results indicate that the proposed ICBO has better computational performance compared with other algorithms.

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