Particle swarm optimization (PSO) is based on biological (and theorical physic) work concerning self-organizaton in animals groups. Up to now, theory explained that animals must adjust their direction in order to set up a group. PSO use this concept to build a set of vectors that will exlpore the search space of an optimization problem, while converging on an optimum.

One key prediction of the theory is a transition between the recruitment of the individuals and the collective motion. This transition "from disorder to order" has been proved in situ by biologists, while studying locusts. They have filmed during 8 hours a group of 5 to 120 desert locusts, in a circular cockpit, and analysed the motions datas. The study shows that, at low density (under 25 individuals/m2), the animals moves independently. When reaching 25 to 60 locusts/m2, they form collective groups, which direction can vary abruptly. Beyond 75 locusts/m2, the coordinated marching is homogen.

While this should not change the use of PSO, which is a simplified model, it is always interesting to consider works talking about this transition between order and chaos, in self-organized systems. Indeed, this transition can also occurs in metaheuristics, and is perhaps interesting for further research, like in dynamical optimization.

From Disorder to Order in Marching Locusts, Buhl et al., Science, Vol. 312. no. 5778, pp. 1402 - 1406, 2 june 2006.