Improved particle swarm optimization algorithm based on niche, crossover and selection operators

An improved particle swarm optimization algorithm based on the niche, crossover and selection operators (NCSPSO) was developed to overcome the problem of the standard PSO in optimizing multimodal function, i.e. being trapped into local minima as well as premature due to the lack of the coordinates variation associated with the best solution for each particle, known as pbest. After the update of the particle velocity and position, the outlier particle was identified in the NCSPSO by comparing the niche number of every particle, with which the crossover and selection operators were employed sequently for those particles, whose personal best values were less than that of the outlier particle. Numerical test results on benchmark functions show the better performance of the NCSPSO compared to the original one. Finally, the NCSPSO was applied to solve higher degree nonlinear equations, which can provide effective and practical solutions to the calculation of intrinsic frequency in the POGO vibration study.