Readit Newsryan-nextmv commented on · Posted by u/ryan-nextmv
The conference is virtual. It runs Monday, September 18 through Wednesday, September 20. Registration is free.
ryan-nextmv commented on “P = NP” Polynomial-Sized LP Models for Hard Cops tsplp.research.uconn.edu/... · Posted by u/mikk14
Even if this paper is correct, the approach is not practical. From table 1 in section 6.2, the LP representation of a 25-city TSP requires 24,580,032 variables and 3,643,825 constraints. Merely formulating that model will require significantly more time than fully optimizing a TSP of that size using an assignment or 2-matching relaxation and adding subtour elimination constraints as they are violated. The former will likely take seconds (or maybe minutes) at that size, while the latter can be accomplished in milliseconds.
ryan-nextmv commented on Ask HN: Do you use an optimization solver? Which one? Do you like it? · Posted by u/ryan-nextmv
I loved the JuMP package in Julia for being able to write models once, then swap in different solvers.
Most open-source solvers don't handle parallelization well, and they lack the latest research on techniques like branch-cutting and heuristics that can speed things up significantly.
In my experience, Gurobi is still leader for linear and MiP solving. But, it's really expensive and the licensing terms seem anachronistic.
SimpleRose.com was a startup working on a new solver, too - I'm curious if anybody has tried it yet?
I haven't looked at JuMP in a while - the last time I tried it was when I was still doing personal blogging (https://ryanjoneil.github.io/posts/2014-07-18-are-we-getting...).
I remember liking JuMP, but Julia itself didn't feel ready yet. Some of the packages had weird behaviors. For example, Gadfly took several minutes to render some of my charts. IIRC when I looked at the source, it was solving a MIP to compute the best bounding box for display purposes.
I should probably check it out again.
Also: agreed regarding Gurobi licensing.