watwatwat123

I just added a list of the supported solvers to the README. Around 20.

I am not aware of any.

Thanks!

I recently restarted development, so I thought I'd repost and see if anyone from HN is interested/has feedback or ideas.

I need to document that better, but rmpk ships with a "ROI optimizer". ROI is an R package that provides bindings to most of the popular solvers: https://roi.r-forge.r-project.org

But I am also working on providing custom bindings to different solvers, to be able to have more control over them. E.g. GLPK: https://github.com/r-opt/GLPKoptimizer

One interesting heuristic is h(x) = 0, which is also [admissible](https://en.wikipedia.org/wiki/Admissible_heuristic) and transforms your A* into an uninformed heuristic as far as I remember.

Last year I read the part about Non-standard evaluation in Hadley Wickham's Book (http://adv-r.had.co.nz/Computing-on-the-language.html) when I thought that this can be used to build a DSL for modelling MIPs. Then I developed a quick PoC over the weekend which evolved into this package. And that initial impulse to work on this topic was probably inspired by the JuMP (https://jump.readthedocs.io/en/latest/) project in julia which I had used for a graph layouting problem before (and I guess by other modelling DSLs I have used / played with in the past).

In general I just like the theory and practical applications of MILPs, however I don't work on these problems in my day job. I am just hobbyist.