I have a multi-objective optimization problem  where I have about 100 millions of lines to maximize or minimize (objective functions).
When I searched about which algorithm should I use, everybody said it depends on the problem and the number of objective functions. The most indicated one was NSGAII, but I read somewhere that NSGAII was not so good for a high number of objectives. Is it true? Which algorithm is the best on my case?
This sounds really crazy.
Here is a plot of the Pareto optimal points of a (discrete) design problem with just 3 objectives:.
I don’t want to guess how this looks with a million of objectives.
- Stackoverflow original post: http://stackoverflow.com/questions/42658957/which-is-the-best-algorithm-to-use-for-multi-objctive-optimization-with-millions
- Visualization of large multi-criteria result sets with plot.ly, http://yetanothermathprogrammingconsultant.blogspot.com/2015/12/visualization-of-large-multi-criteria.html