Dynamic-probabilistic particle swarms

摘要

The particle swarm algorithm is usually a dynamic process, where a point in the search space to be tested depends on the previous point and the direction of movement. The process can be decomposed, and probability distributions around a center can be used instead of the usual trajectory approach. A version that is both dynamic and Gaussian looks very promising.