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RISS 인기검색어
- 검색키워드
- 저자 : Saeed Gholizadeh (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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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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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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Optimum design of steel frame structures by a modified dolphin echolocation algorithm
Saeed Gholizadeh,Hamed Poorhoseini 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.55 No.3
Dolphin echolocation (DE) optimization algorithm is a recently developed meta-heuristic in which echolocation behavior of Dolphins is utilized for seeking a design space. The computational performance of meta-heuristic algorithms is highly dependent to its internal parameters. But the computational time of adjusting these parameters is usually extensive. The DE is an efficient optimization algorithm as it includes few internal parameters compared with other meta-heuristics. In the present paper a modified Dolphin echolocation (MDE) algorithm is proposed for optimization of steel frame structures. In the MDE the step locations are determined using one-dimensional chaotic maps and this improves the convergence behavior of the algorithm. The effectiveness of the proposed MDE algorithm is illustrated in three benchmark steel frame optimization test examples. Results demonstrate the efficiency of the proposed MDE algorithm in finding better solutions compared to standard DE and other existing algorithms.
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Topology optimization of nonlinear single layer domes by a new metaheuristic
Saeed Gholizadeh,Hamed Barati 국제구조공학회 2014 Steel and Composite Structures, An International J Vol.16 No.6
The main aim of this study is to propose an efficient meta-heuristic algorithm for topology optimization of geometrically nonlinear single layer domes by serially integration of computational advantages of firefly algorithm (FA) and particle swarm optimization (PSO). During the optimization process, the optimum number of rings, the optimum height of crown and tubular section of the member groups are determined considering geometric nonlinear behaviour of the domes. In the proposed algorithm, termed as FA-PSO, in the first stage an optimization process is accomplished using FA to explore the design space then, in the second stage, a local search is performed using PSO around the best solution found by FA. The optimum designs obtained by the proposed algorithm are compared with those reported in the literature and it is demonstrated that the FA-PSO converges to better solutions spending less computational cost emphasizing on the efficiency of the proposed algorithm.
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