Abstract
In this paper, a new efficient method to solve the structural optimization problems with the static and dynamic constraints using Genetic Algorithms (GAs) was proposed. With this method, the static equilibrium equation and dynamic equation have no need to be solved by conventional methods resulting in saving the huge computing time which accounts for the most part of the computation in structural optimization. In order to achieve this goal, the concept of generalized design variables was introduced. The number of the variables becomes larger when the new method is applied to real-world engineering problems. To save the computing storage, in this paper, the floating point representation to the string of solution was used. Since many problems reach their optimal point on or near the boundary of constraints, the boundary mutation was introduced to speed up the convergence of the method. To improve the fine local tuning capabilities of this method, the non-uniform mutation was also used. The effect of the boundary mutation and non-uniform mutation on the performance of the GA was examined. A simple numerical example was given to illustrate applicability of this method.
