1. Introduction
Optimization has been a popular research topic for decades. Particle Swarm Optimization (PSO) is now established as an efficient optimization algorithm for static functions in a variety of contexts [1]. With the dynamic optimization problems appearing, the PSO is also applied in dynamic optimization [2]. The dynamic optimization problems have been changing over time, which causes changes in the position of optima as well as the characteristics of the search space. This leads to the fact that existing optima may disappear, while new optima may appear. Optimization under the dynamic environments is a challenging task that attracts great attention.