Optimal Design of Planar Frame Structures Using an Optimization Algorithm Based on Global Sensitivity Analysis

The main aim of this paper is to present a new single-solution metaheuristic algorithm so-called global sensitivity analysis based (GSAB) algorithm for discrete sizing optimization of steel frames. In the GSAB method, the single solution moves towards specified regions determined using the sensitivity indicator of the variables. In comparison to population-based meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach first the highly sensitive variables of solution and then the less sensitive ones are iteratively changed in the search space, therefore the global convergence of algorithm is accelerated. In order to evaluate the performance of the GSAB algorithm, three planar frame benchmark problems are conducted. The experimental results show that the proposed method performs better than, or at least as well as other population-based meta-heuristic algorithms, especially in decreasing the number of fitness function evaluation.