On Sun, Dec 12, 2021 at 3:44 PM Julian Hall <jajhall at ed.ac.uk>
wrote:>
> Dear All,
>
> I am leading the development of HiGHS, which is now the top performing open
source linear optimization software on the industry standard benchmarks. In
particular, our MIP solver out-performs SCIP, and is way ahead of the COIN-OR
solver Cbc.
>
> HiGHS solves LPs via simplex or interior point, MIPs via branch-and-cut,
and QPs via an active set method.
>
> We were wondering what interest there would be in developing an R interface
to HiGHS. I'm not an R user, but have done a bit of searching and see
references to Rsymphony and an interface to Lpsolve.
>
> Performance-wise Lpsolve is very poor, but I know that it has a community
of devoted followers. I've not seen benchmark results for Symphony, but I
know that Cbc is the preferred COIN-OR MIP solver when it comes to general
performance. And, as I observed, the performance of HiGHS is way better than
Cbc.
>
> Are people in the R community tearing their hair out over the performance
of software requiring the solution of LPs or MIPs?
>
> Would a significantly better LP/MIP solver be valuable to the R community?
>
> Thanks,
>
> Julian
> --
> Dr. J. A. Julian Hall, Reader, School of Mathematics,
> University of Edinburgh, James Clerk Maxwell Building,
> Peter Guthrie Tait Road, EDINBURGH, EH9 3FD, UK.
> Room: 5418 Phone: [+44](131) 650 5075 Email: J.A.J.Hall at
ed.ac.uk<mailto:J.A.J.Hall at ed.ac.uk>
> Web: https://www.maths.ed.ac.uk/school-of-mathematics/people/a-z?person=47
> [HiGHS]<http://www.highs.dev>
>
> My working hours may not be your working hours. Do not feel pressure to
reply to this email outside your working hours.
> The University of Edinburgh is a charitable body, registered in Scotland,
with registration number SC005336. Is e buidheann carthannais a th? ann an
Oilthigh Dh?n ?ideann, cl?raichte an Alba, ?ireamh cl?raidh SC005336.
Hello, Julian.
I cannot speak for the R community, but as someone who needs
optimization on a regular basis, this sounds intriguing. The fact that
HiGHS appears to be FLOSS, and thus usable as-is in the corporate
setting, appeals to those of us who use R in industry. Would you have
any statistics on how the solvers in HiGHS compare with similar ones
currently available in R, specifically the following in NLOPT [1]
(which is called through nloptr): SLSQP (gradient-based) and COBYLA
(gradient-free) both of which support equality and inequality
constraints, and MMA/CCSA (gradient based) which supports inequality
constraints? As for integer or mixed integer programming, I believe
that there is a lot of room for improvement in R. Personally, I've
resorted to using DEOptim with the "fnMap" entry calling a round
function similar to [2]. So speaking for myself, giving richer options
for optimization is a good thing, especially if the installation
procedure can be simplified!
Thank you,
Avi
[1] https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/
[2]
https://stackoverflow.com/questions/42197353/how-to-set-integer-constraint-using-fnmap-in-deoptim-r