Empirical study of bound constraint-handling methods in Particle Swarm Optimization for constrained search spaces

This paper presents an empirical study comparing the performance of thirty-five boundary constraint-handling methods (BCHM) for PSO in constrained optimization, which were tested in a set of thirty-six well-known constrained problems. Each BCHM is composed as an hybrid consisting of one position update techniques and one velocity update strategy. Results show that the hybrid method that relocates the particles through a position update technique called Centroid and modifies its velocity through the Deterministic Back strategy is able to promote better final results and improving both, the approach to the feasible region and the ability to generate better feasible solutions.