I use lp_solve (from R) currently to solve reasonably large (but sparse) LPs/IPs for planning/optimization and other Operations Research flavored problems that arise at work.
Broadly speaking, it works well, and i like working in R, but i know that the models we consider will need to evolve at least to being quadratic in nature (with the possibility of being non-convex in general).
I'd like to know what the "industry standard" is in this space: should i not look beyond the AMPL/CPLEX combination (and invest some time there) ? Additional questions: Which of GAMS/AMPL is a better choice? (not proficient in either, but know what i need functionally: sparse matrix support for example) For really large LPs/QPs/IPs, how well does CPLEX scale across clusters? How much of a curve is there to be able to setup/run such a cluster?