New self-organising hierarchical PSO with jumping time-varying acceleration coefficients

Without doubt, one of the powerful and effective optimiser in the area of evolutionary algorithms and improved particle swarm optimisation (PSO) is the self-organising hierarchical PSO with time-varying acceleration coefficients (HPSO-TVAC) which has been implemented successfully in the many problems (cited by 2430 until now). Real-world problems are multi-variable problems with real-world different complexities. The classical HPSO-TVAC optimisation technique often converges to local optima solution for some of the real-world problems. Therefore, finding efficient modern versions of the PSO algorithm (here HPSO-TVAC) to solve the real-world problems are absorbing a growing attention in recent years. A novel HPSO-TVAC algorithm for real-world optimisation is proposed. The simulation results show that proposed HPSO-TVAC new version, NHPSO-JTVAC, is powerful and very competitive for real-world optimisation.