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 install. 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.