[mlpack] GSoC 2018: Particle Swarm Optimization

[Chintan Soni]

Hello Marcus,

> Do you mean something like "COPSO: Constrained Optimization via PSO
> algorithm"
> by A. H. Aguirre et al.?

I was actually referring to constraint handling techniques, like
section 3 of the paper you mentioned covers (I guess the question was
poorly phrased, my bad). That being said, this paper actually turned
out to be quite useful because:
1. It covers a few constraint handling techniques, which I can dig deeper into.
2. From the paper: "He and Prempain used a “fly-back” mechanism that
returns an unfeasible particle to its previous feasible position [23].
An important drawback of this technique is the requirement of an
all-feasible initial population."

This flyback mechanism is exactly what the MOPSO paper suggested to
handle constraints, so I might also have to look into improvements on
that.

Thanks for the help!

Regards,
Chintan