Automatic Design of Large-Scale Trusses: A Comparison Between Derivative-Free Algorithms (2020)
The design of steel trusses is a frequent problem in civil engineering, which requires the experience of the design engineer to achieve a structural solution with good performance and that can satisfy the established needs. In recent years, the design of these systems has been supported by the application of various methods of optimization, which allow optimal solutions, meeting the proposed design objectives, automatically and in a shorter time. This research presents the application of a series of multiobjective metaheuristic algorithms for the automatic design of large-scale trusses. The NSGA-II, MOPSO and AMOSA algorithms were applied and the structures reported in the literature were considered to be made up of a high number of elements. The performance of the algorithms was evaluated based on the computational cost, the hypervolume criterion and the behavior that the algorithms have when increasing the amount of iterations per optimization cycle. The search space used in the optimization was discrete, restricted by the W steel profiles available in the Colombian market. The results obtained show that, for the proposed problems, the MOPSO algorithm is the most efficient, followed by the AMOSA and the NSGA-II which showed a higher computational cost. Finally, it is worth mentioning that the calculation times were less than one hour, for trusses close to a thousand elements.