Truss sizing optimization with a diversity-enhanced cyclic neighborhood network topology particle swarm optimizer

Abstract

This study presents a reliable particle swarm optimizer for sizing optimization of truss structures. This population-based stochastic optimization approach is based on the principle that each particle communicates its position and function value to a number of successively numbered neighboring particles via a fixed cyclic interaction structure. Therefore, such a neighborhood structure changes the movement pattern of the entire swarm, and allows each particle's movement not to be driven by one global best particle position, which enhances the diversification attitude. Further, by transforming the objective function, it is possible to steer the search towards feasible regions of design space. The efficiency of the proposed approach is demonstrated by solving four classical sizing optimization problems of truss structures.