Optimization of truss structures using metaheuristics

Abstract

    Metaheuristic algorithms have been widely used for structural optimization design because of their powerful ability to find globally optimal solutions. However, the efficiency of these algorithms depends on the characteristics of the class of optimization problems considered. Therefore, understanding the advantages and disadvantages of optimization algorithms is essential to apply them effectively in the design work. In this paper, three modern metaheuristic algorithms are studied and applied to the optimal design of truss structures using nonlinear inelastic analysis, including micro-genetic algorithm (micro-GA), Rao optimization algorithm, and the adaptive differential evolutionary algorithm (EapDE). The 72-bar space steel bar with 16 design variables is considered for both discrete and continuous variables. The results show that EapDE finds the optimal results and speed better than the other two algorithms