After experimenting with various FIPS topologies, Mendes, Kennedy, and Neves wrote, "The very worst FIPS conditions in the study were the UAll and All topologies, where the particle is truly fully informed, gathering information from every single member of the population. The best were the Ring and Square versions, where the particle has three and five neighbors (counting itself), respectively, plus their U-versions, which subtract one" [1]. Therefore, using a literally fully informed model would probably not be the best approach unless recent research suggests doing so.

The URing topology was the best performer in terms of solution quality - with the only down side being its more cautious rate of convergence [1]; hence, URing is the FIPS model of choice unless the application is considerably time sensitive. But since basic Lbest PSO uses the same Ring topology, the URing FIPS should simply be regarded as a validation of the basic Lbest formulation.

I like the experiments with which Kennedy has been involved regarding different PSO schemata [1, 3, 4, 5, 6]; they are akin to a thorough exploration of the search space before settling on any one PSO type. It is quite interesting that the simple ring topology performed so well.

For the reasons explained above, the fully informed model will not be added to the toolbox; but I would be happy to guide a young researcher to make the contribution.

[1] R. Mendes, J. Kennedy, and J. Neves, "The Fully Informed Particle Swarm: Simpler, Maybe Better", IEEE Transactions on Evolutionary Computation, vol. 8, pp. 204-210, June 2004

[2] http://www.georgeevers.org/thesis.pdf

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[3] R. C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Micro Machine and Human Science, MHS '95., Proceedings of the Sixth International Symposium on, Nagoya, Japan, 1995, pp. 39-43.

[4] J. Kennedy, The particle swarm: social adaptation of knowledge. Proceedings of IEEE International Conference on Evolutionary Computation, Indianapolis, IN, 1997, pp. 303-308

[5] J. Kennedy, "Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance," Proceedings of the 1999 Congress on Evolutionary Computation, Washington, DC, 1999

[6] M. Clerc and J. Kennedy, ""The particle swarm - explosion, stability, and convergence in multidimensional complex space"," IEEE Transactions on Evolutionary Computation, vol. 6, pp. 58-73, Feb. 2002.