Cold formed steel (CFS) has many advantages over other construction materials.
CFS members are lightweight. They weigh up to 30-35% less than their wood
counterparts.. This makes CFS members economical and the same time very easy to erect
and inst
all. They may be shaped (cold-bent) to nearly any open cross section. This allows
for the use of optimization technique’s to find optimal shapes for the members’ cross
sections.
The research aims to show the genetic algorithm's ability in determining the optimum
dimensions cold formed C section. To do so, the optimum design mathematical
formulation was formulated by adding the manufacturing constraints that reflect the
section folding operations in addition the geometrical and structural constraints.
The research found that the genetic algorithm is effective tool in finding the best
solution to this issue, as it showed its ability to deal with asymmetric section through
reaching solutions conform to the basic principles of mechanics of material.
The algorithm is adjustable, so that it can implement the design restrictions which are
compatible with any codes or any manufacturing requirements imposed by modulation
techniques.