Title of article :
Particle Swarm Optimisation with Improved Learning Strategy
Author/Authors :
Lim, Wei Hong Universiti Sains Malaysia, Engineering Campus - School of Electrical and Electronic Engineering, Malaysia , Mat Isa, Nor Ashidi Universiti Sains Malaysia, Engineering Campus - School of Electrical and Electronic Engineering, Malaysia
From page :
27
To page :
48
Abstract :
In this paper, a new variant of particle swarm optimisation (PSO) called PSO with improved learning strategy (PSO-ILS) is developed. Specifically, an ILS module is proposed to generate a more effective and efficient exemplar, which could offer a more promising search direction to the PSO-ILS particle. Comparison is made on the PSO-ILS with 6 well-established PSO variants on 10 benchmark functions to investigate the optimisation capability of the proposed algorithm. The simulation results reveal that PSO-ILS outperforms its peers for the majority of the tested benchmarks by demonstrating superior search accuracy, reliability and efficiency.
Keywords :
Particle swarm optimisation , improved learning strategy , global optimisation , metaheuristic search , swarm intelligence
Journal title :
Journal of Engineering Science
Journal title :
Journal of Engineering Science
Record number :
2587876
Link To Document :
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