Degree Name

Master of Engineering (Hons.)


Faculty of Engineering


The field of optimal design of engineering structures has been revolutionised by the rapid development of computer technology in the past few decades, which has enabled the design and analysis to be achieved with much greater speed and accuracy than ever before. A number of design methodologies have been developed and are in use for the optimum design of structural systems. In the last decade, the use of evolutionary algorithms, especially genetic algorithms (GAs) to optimise the design of structures has received much research attention mainly because of their simplicity, global perspective, and inherent parallel processing. Furthermore, in GA the gradient of the objective function and the constraint functions are not needed to find optimal solutions. Therefore GAs have capability to handle any design problems that may involve non-differentiable objective fiinction and/or a combination of continuous, discrete, and integer design parameters. Many research studies have reported the solution of truss structure optimisation problems through GAs in recent years. In all the recent research studies only linear analysis was considered to determine the response of the structure to the applied load in the optimisation process using GA. The linear analysis for some structures such as longspan and slender structures may not be applicable because of the geometric non-linear behaviour of the structure, which may be due to the presence of large deflection. These structures require non-linear analysis to obtain their behaviour and response prediction under the external loading, thus it has become mandatory to carry out geometric nonlinear analysis of long-span and slender structures such as suspension bridges.



Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.