Eccentricity optimization of NGB system by using multi-objective genetic algorithm

被引:1
作者
Yazdi, H. Mosalman [1 ]
Ramli Sulong, N.H. [1 ]
机构
[1] Department of Civil Engineering, Faculty of Engineering, University of Malaya
关键词
Brace; Genetic algorithm; Multi object; Seismic load;
D O I
10.3923/jas.2009.3502.3512
中图分类号
学科分类号
摘要
In this study, a new method for designing a particular braced system by using multi-objective genetic algorithm is proposed. This type of braced system, which is called non-geometric braced system are mostly used in seismic areas and it allows architects to have more openings in the panels. Non-straight diagonal member of this system introduces eccentricity and it is connected to the corner of the frame by a third member. In designing this system, designers often use trial and error method to locate the connection point of the brace elements by considering various parameters which affect the design such as opening and frame dimensions, cross section areas of brace elements and the location of brace element connection. Hence, finding the best connection point with maximum stiffness and minimum weight of brace elements with conventional methods is not trivial. In this study, a multi-object genetic algorithm is proposed in determining the best selection for connection point and also the brace elements' cross section area proportions which is the key rule in determining the stiffness of the system. Boundary equations are set by introducing feasible area to avoid improper individuals followed by utilization of some operators such as selection, mutation, crossover and elite genetic algorithm. Based on the plain aggregate approaches for transforming the objective vector in scalar, some modifications are proposed to assist designers in making decision on prioritizing between the frame stiffness and brace frame weight in their design. © 2009 Asian Network for Scientific Information.
引用
收藏
页码:3502 / 3512
页数:10
相关论文
共 23 条
[1]  
Aiello G., Enea M., Galante G., A multi-objective approach to facility layout problem by genetic search algorithm and electre method. Robotics Comput, Integrated Manuf, 22, pp. 447-455, (2006)
[2]  
Aristizabal-Ochoa J.D., Disposable knee bracing: Improvement in seismic design of steel frames, J. Struct. Eng., 112, pp. 1544-1552, (1986)
[3]  
Bosco M., Rossi P.P., Seismic behaviour of eccentrically braced frames, Eng. Struct, 31, pp. 664-674, (2009)
[4]  
Coley D.A., An Introduction to Genetic Algorithms for Scientists and Engineers, (1999)
[5]  
Fonseca C.M., Fleming P.J., An overview of evolutionary algorithms in multi objective optimization, Evolutionary Computation, 3, pp. 1-16, (1995)
[6]  
Gero M.B.P., Garcia A.B., del Coz Diazb J.J., A modified elitist genetic algorithm applied to the design optimization of complex steel structures, J. Construct. Steel Res., 61, pp. 265-280, (2005)
[7]  
Goldberg D., Genetic Algorithms in Search Optimization and Machine Learning, (1989)
[8]  
Haupt R.L., Haupt S.E., Practical Genetic Algorithms, (2004)
[9]  
Holland J.H., Adaptation in Natural and Artificial Systems, (1975)
[10]  
Kang J.H., Kim C.G., Minimum-weight design of compressively loaded composite plates and stiffened panels for postbuckling strength by genetic algorithm, Comp. Struct., 69, pp. 239-246, (2005)