Optimum Design of Skeletal Structures Using PSO-Based Algorithms

Abstract

The particle swarm optimization with an aging leader and challengers (ALC-PSO) algorithm is a recently developed optimization method which transplants the aging mechanism to PSO. The ALC-PSO prevents premature convergence and maintains the fast-converging feature of PSO. In this paper, a harmony search-based mechanism is used to handle the side constraints and it is combined with ALC-PSO, resulting in a new algorithm called HALC-PSO. These two algorithms are employed to optimize different types of skeletal structures with continuous and discrete variables. The results are compared to those of some other meta-heuristic algorithms. The proposed methods find superior optimal designs in all problems investigated, illustrating the capability of the present methods in solving constrained problems. The convergence speed comparisons also reveal the fast-converging feature of the presented algorithms.