New self‐organising hierarchical PSO with jumping time‐varying acceleration coefficients. Issue 20 (11th September 2017)

• Record Type: Journal Article
• Authors: Ghasemi, M.; Aghaei, J.; Hadipour, M.
• Is Part Of: Electronics letters. Volume 53:Issue 20(2017)
• Page Start: 1360
• Page End: 1362
• Publication Date: 2017-09-11
• Subjects: particle swarm optimisation -- evolutionary computation -- acceleration -- time‐varying systems -- multivariable control systems -- self‐adjusting systems -- optimal control; particle swarm optimisation -- self‐organising hierarchical PSO -- jumping time‐varying acceleration coefficients -- evolutionary algorithms -- NHPSO‐JTVAC -- multivariable problems -- local optima solution -- real‐world optimisation; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2017.2112
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : 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.