scholarly journals MINIMUM WEIGHT DESIGN METHOD CONTROLLED BY STRUCTURAL PERFORMANCE FOR PLANE ELASTIC STEEL FRAME USING NEURAL NETWORK

1996 ◽  
Vol 61 (489) ◽  
pp. 147-153 ◽  
Author(s):  
Kazutoshi TSUTSUMI
Keyword(s):  
Neural Network ◽  
Design Method ◽  
Minimum Weight ◽  
Steel Frame ◽  
Structural Performance ◽  
Minimum Weight Design ◽  
Weight Design

Coefficient Distribution Method for Minimum Weight Design of Large-Span Determinate Trusses

2010 ◽  
Vol 163-167 ◽  
pp. 2424-2430
Author(s):  
Wen Feng Du ◽  
Zhi Yong Zhou ◽  
Sheng Xiang Wang ◽  
Fu Dong Yu
Keyword(s):  
Design Method ◽  
Minimum Weight ◽  
Cauchy Inequality ◽  
Calculation Formula ◽  
Minimum Weight Design ◽  
Distribution Method ◽  
Large Span ◽  
Coefficient Distribution ◽  
Study Results ◽  
Weight Design

The minimum weight design method of large-span statically determinate trusses satisfying the displacement constraint is studied. The displacement calculation formula is provided, and the critical condition of minimum weight design satisfying the condition of allowed displacement is educed using Cauchy inequality. The distribution coefficient, which is used to obtain the minimum weight design, is defined and the coefficient distribution method is proposed. An engineering example is analyzed using the coefficient distribution method above, and the compared results are discussed. Study results show that the proposed method, coefficient distribution method, is correct，reliable and effective.

scholarly journals Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Hyo Seon Park ◽  
Eunmi Kwon ◽  
Yousok Kim ◽  
Se Woon Choi
Keyword(s):  
Genetic Algorithm ◽  
Minimum Weight ◽  
Hybrid Genetic Algorithm ◽  
Optimization Methods ◽  
Steel Frame ◽  
Convergence Properties ◽  
Minimum Weight Design ◽  
Frame Buildings ◽  
Steel Frame Buildings ◽  
Weight Design

Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.

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