2015/11/19 by J. Michael Herrmann, Herrmann, J. Michael, Adam Erskine +3
Computer Science · #Metaheuristic Optimization Algorithms Research #Advanced Multi-Objective Optimization Algorithms #Evolutionary Algorithms and Applications
paper · pdf · doi:10.48550/arxiv.1511.06248
Particle swarm optimisation is a metaheuristic algorithm which finds reasonable solutions in a wide range of applied problems if suitable parameters are used. We study the properties of the algorithm in the framework of random dynamical systems which, due to the quasi-linear swarm dynamics, yields analytical results for the stability properties of the particles. Such considerations predict a relationship between the parameters of the algorithm that marks the edge between convergent and divergent behaviours. Comparison with simulations indicates that the algorithm performs best near this margin of instability.