Optimization of cold formed steel structures using genetic algorithm in a BIM environment

Abstract

Due to the rapid technology advancement, the construction industry is being challenged to achieve a high level of performance. The use of BIM platform has enhanced the productivity through the improvement of the knowledge sharing and interface between the disciplines involved in the construction process. In this context, the present study proposes a methodology based on genetic algorithm to integrate an automatic structural design of Cold Formed Steel (CFS) structures in a BIM platform. CFS refers to a manufacturing process where metallic-coated sheet steel is rollformed at ambient temperature into structural elements of various cross-section shapes used for low and mid-rise buildings. In Algeria, the use of CFS profiles as the primary structural members in buildings is in its beginning, the first CFS multi-storey buildings were erected early last decade. The concept of the proposed algorithm is based on a multi-objective optimization process that generates a best structural layout for a given BIM model of an architectural configuration. For illustrative purposes, the proposed methodology is applied to several prototype buildings and the obtained results have demonstrated that, in the case of the considered architectural configurations, the proposed approach is very efficient in generating optimal structures, which are consistent with the predefined criteria and fulfilling the structural design requirements.