Wouldn’t it be nice to have a single package in Julia hosting benchmark optimization problems for different classes of optimization to make it easier for solver developers to test their solvers and benchmark them? The problem is that there are too many benchmarking sets e.g. Netlib, MIPLIB, CUTEst, SDPLib, CSPLib, MacMINLP, GAMS World, COCONUT, mintOC, minlp.org, POLIP, CBLIB, and CEC. These problems come in all sorts of file formats, e.g. gms, ams, mod, and mps to name a few. So I wonder if some parsers have been written for some of these formats to say read the optimization problems into a JuMP model and then the solver developer can operate on the JuMP model struct directly without having to worry about where it came from. Of course it would be nearly insane to try and write all these problems from scratch in JuMP syntax because there are too many of them, and some are based on big data files.
So I wonder what the optimization solver developers in this forum think, is this doable, pointless, on the agenda, or perhaps already partially done? Any advice or pointer is appreciated.