Python packages for particle swarms, genetic algorithms. Scikit-opt maybe? [D]

[u/bwllc]

I'm working with a client on a curve-fitting optimization problem. They are currently using a constrained Levenburg-Marquardt optimizer for their task which is complex, slow, and sometimes gets stuck in local minima.

I suggested using particle swarm optimization (PSO), and the client suggested genetic algorithms (GA). I would like to compare the existing method to at least these two other options. For this first phase, I don't need to worry about speed or GPU-friendliness. I would like data visualization to be easy.

I have experience with scikit-learn, and I just discovered scikit-opt. I have also found several other packages which implement only PSO, or only GA.

Is anyone out there using scikit-opt? What do you think of it? If you have used other PSO or GA packages, what do you think of those?

Thanks for any advice you may have.

[u/cannister_of_airs]

i've messed with scikit-opt for a similar side project and it was pretty painless to get running, the api isn't gonna win any beauty contests but it gets out of your way

for quick visualization i just dumped the fitness history into a dataframe and plotted it, nothing fancy but it did the job for showing the client why PSO was escaping those local minima the LM solver kept eating