A swarm optimizer with modified feasible-based mechanism for optimum structure in steel industry

This study proposes a swarm optimizer with a modified feasible-based mechanism approach for finding an optimum design for steel frames. The proposed optimization approach addresses the problem of stagnation possibility in the traditional particle swarm optimization in which none of the particles tries to explore a position better than the previous best position for multiple numbers of iterations. This method is based on accelerated particle swarm optimization and big bang-big crunch optimization algorithms. In addition, a modified feasible-based mechanism is used to correct the particle's position. The new method's performance is evaluated by solving two structural problems to minimize the weight of steel frames. The results show that the optimized designs obtained by the proposed algorithm are better than those found by the competing algorithms from the literature.