抄録
In the previous work, the stability condition of the particle swarm optimization algorithm has been derived by linear matrix inequality techniques. This paper provides an alternative representation of the stability condition, which can be checked more shortly and accurately than that in the previous work. The stability condition is described by nonlinear scalar inequalities. Also, we present a condition related to a decay rate of the particle swarm optimization algorithm in terms of nonlinear scalar inequalities. Numerical experiments are given to show that the largest lower bound of the decay rate can be used as a measure of convergence speed of the particle swarm optimization algorithm.
