Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm

Yazdi, H.M. and Ramli Sulong, N.H. (2009) Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm. Journal of Applied Sciences, 9 (19). pp. 3502-3512. ISSN 1812-5654, DOI https://doi.org/10.3923/jas.2009.3502.3512.

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Official URL: http://scialert.net/abstract/?doi=jas.2009.3502.35...

Abstract

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.

Item Type: Article
Funders: UNSPECIFIED
Uncontrolled Keywords: Eccentricity Optimization; NGB System; Multi-Objective Genetic Algorithm
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 16 Dec 2015 02:20
Last Modified: 16 Dec 2015 02:20
URI: http://eprints.um.edu.my/id/eprint/15086

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