In this research, a Genetic Algorithm (GA) has been developed and the well-known one-dimensional bin packing problem (BPP) has been implemented within the structural optimization process. The Objective Function formulation lies in a marked change of the paradigm in which the target function is represented by the amount of steel required by the factory instead of the structural cost (e.g. weight). The best design is obtained by varying the geometry properties of the members and the cross-section assignation ensuring optimal stock of existing elements. Finally, the structural cost and the Carbon emission are calculated for a spatial reticular dome. The mass of the waste with respect to the mass of the stock, Mwaste/Mstock, is evaluated by adopting both the cutting Stock approach and the traditional approach. The former leads to a waste saving that is almost twice that obtained from the latter. However, no significant differences in terms of carbon emission can be observed by comparing the two approaches.