A hybrid algorithm for continuous optimisation
Nathan Thomas, M. B. Reed · 2009
An effective particle swarm - quasi-Newton hybrid for the optimisation of continuous functions is developed, which is shown to work well on a range of test problems. This method exploits the global exploration abilities of the PSO algorithm and the fast convergence of the quasi-Newton method. New switching heuristics between the quasi-Newton and PSO methods are introduced, with the update pairs being used to generate new particles. The new hybrid, called L-PSO, is shown to be effective in obtaining the global minimum on a range of test problems, and outperforms previous hybrids with which it is compared.