Another research trend is to try andto alleviate premature convergence (that is, optimization stagnation), e.g. by reversing or perturbing the movement of the PSO particles,<ref name=evers09thesis/><ref name=lovbjerg02extending/><ref name=xinchao10perturbed/><ref name=xzy02dpso/> another approach to deal with premature convergence is the use of multiple swarms<ref>{{cite journal | last1 = Cheung | first1 = N. J. | last2 = Ding | first2 = X.-M. | last3 = Shen | first3 = H.-B. | year = 2013 | title = OptiFel: A Convergent Heterogeneous Particle Sarm Optimization Algorithm for Takagi-Sugeno Fuzzy Modeling | journal = IEEE Transactions on Fuzzy Systems | volume = 22| issue = 4| pages = 919–933 | doi = 10.1109/TFUZZ.2013.2278972 | s2cid = 27974467 }}</ref> ([[multi-swarm optimization]]). The multi-swarm approach can also be used to implement multi-objective optimization.<ref name=nobile2012 /> Finally, there are developments in adapting the behavioural parameters of PSO during optimization.<ref name=zhan09adaptive/><ref name=nobile2017/>
