A Genetic Algorithm based Optimum Bracing Design of Non-Sway Tall Steel Frames

2009 ◽  
Author(s):  
E.S. Kameshki ◽  
M.P. Saka
Keyword(s):  
Genetic Algorithm ◽  
Steel Frames

Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and irregular steel frames

2020 ◽  
Vol 14 (5) ◽  
pp. 1110-1130
Author(s):  
Mohammad Sadegh Es-Haghi ◽  
Aydin Shishegaran ◽  
Timon Rabczuk
Keyword(s):  
Genetic Algorithm ◽  
Structural Design ◽  
Steel Frames

Weight Optimization of Steel Frames Using Genetic Algorithm

2002 ◽  
Vol 5 (2) ◽  
pp. 99-111 ◽  
Author(s):  
Ribelito F. Torregosa ◽  
Worsak Kanok-Nukulchai
Keyword(s):  
Genetic Algorithm ◽  
Steel Frames ◽  
Optimization Procedure ◽  
Optimization Techniques ◽  
Weight Optimization ◽  
Discrete Variables ◽  
Design Problems ◽  
Plane Frames ◽  
Population Sizes ◽  
A New Technique

Genetic Algorithm (GA) is a new technique in optimization procedure that works best in design problems with discrete variables. It employs the survival of the fittest philosophy in determining the optimum combination. GA optimization procedure is applied to weight optimization of steel plane frames subjected to different load cases. Database of steel beam sizes is provided as the discrete variables. Both elitist and non-elitist search procedures are used to optimize the total weight of steel frames. Crossover types used are 20- and 50-percent uniform. Optimization result using population sizes 10, 20, and 40 are compared. Elitist search procedure showed superior results when compared to non-elitist for higher population sizes search because of its faster convergence rate. Performance of non-elitist is superior when using lesser population sizes. To examine the performance of genetic algorithms, case studies are conducted by varying material groups and the results are compared with the results from other optimization techniques. Genetic optimization showed superior results when compared to other techniques especially to problems with few material groupings.

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