Fuzzy dynamic turning for particle swarm optimization with weighted particle

This study proposes a fuzzy dynamic turning (FDT) strategy to adjust inertia weight of the enhanced particle swarm optimization incorporating a weighted particle (EPSOWP). In the proposed study, EPSOWP has two principal updating search behaviors which are switched alternately. One of the two behaviors includes the term w×v(t) where w is the inertia weight and v(t) is the velocity. The term w×v(t) gives a search direction based on the particle flying velocity of the last generation. Moreover, a good inertia weight could provide an excellent search direction. Therefore, we use fuzzy reasoning technique to turn the inertia weight of EPSOWP dynamically. The simulation results show that the proposed EPSOWP has outstanding performance on benchmark functions.