Optimization Solver as a Service • Hacker News Board

Re: Optimization Solver as a Service

#11

Post by LPisGood » Sun, Jul 12, 2026, 1:35 AM UTC

shoo wrote: post #8

I'm not a potential customer for this, but i have worked on a few commercial projects involving combinatorial optimisation. Misc thoughts: - I'm not familiar with the LABS problem, but the LABS benchmark page is interesting & compares against Gurobi. I'd be curious to see how an existing commercial non-mip approximate solver such as Hexaly (formerly LocalSolver) compares here. - the other two benchmarks aren't very c…

Does anyone use Hexaly for any serious work? If so, why? There seem to be many better alternatives out there.

Re: Optimization Solver as a Service

#12

Post by cchianel » Sun, Jul 12, 2026, 2:21 AM UTC

uoaei wrote: post #10

cchianel wrote: post #7

Earlier quoted context omitted.

I personally disagree with "no free lunch"; (for the uninitiated, "no free lunch" refer to the fact for any deterministic algorithm, there exist a problem that will force the algorithm to go through the entire solution space to find the optimal solution, with every single other possible algorithm beating it ( https://en.wikipedia.org/wiki/No_free_lunch_theorem )). For many planning problems, finding a good enough sol…

No free lunch theorem has nothing to say about approximate solutions, so I'm really not sure what you're going on about. OR-tools is almost exclusively linear programming which according to its strict assumptions converges more or less trivially, assuming a correctly composed program. Which means if you're paying for it "as a service" you all but deserve to lose that money. > Different algorithms are better for diffe…

Look at it this way: I am arguing against "No Free Lunch theorem says an optimization algorithm cannot solve all problems because for some problems it performs worse than other algorithms"; I am arguing approximate solutions are good enough, and in practice a wide variety of optimization algorithms find good enough solutions despite being worse than others algorithms for the problem class. Moreover, some algorithms/solvers can be configured, which fundamentally change the direction the solving takes (for example, a custom phase that uses your domain knowledge of the particular problem to get a good enough initial solution to be improved upon) (Side note: I am NOT affiliated with this post/project; from the website I don't really see a value add for it, especially since the site is lacking so many details).

Re: Optimization Solver as a Service

#13

Post by DannyBee » Sun, Jul 12, 2026, 3:17 AM UTC

NEOS will let you run this stuff on cplex/gurobi/etc (IE much faster than the backends behind quicopt), for free, is integrated with pyomo/etc, and has like an 8 hour time limit.

Often, the difference on "harder" problems is 10x or more.

I have problems that gurobi solves in 30 seconds that take 15 minutes or more for ~every non-commercial solver (or-tools, HIGHS, ipopt, etc).

But right now, this wouldn't even be interesting to me to use even if they actually were fronting commercial solvers, because they can't actually run it any faster and having this ".solve" API does nothing - pyomo already does that for me in practice.

Re: Optimization Solver as a Service

#14

Post by whatever1 » Sun, Jul 12, 2026, 5:19 AM UTC

We do have standard benchmarks in the field. Hans Mittelman maintains a library. No idea why they did not bother to run them.

https://plato.asu.edu/guide.html

Their website has just 3 cherry picked instances and claim complete dominance.

Re: Optimization Solver as a Service

#15

Post by luiwammus » Sun, Jul 12, 2026, 5:22 AM UTC

LPisGood wrote: post #11

shoo wrote: post #8

I'm not a potential customer for this, but i have worked on a few commercial projects involving combinatorial optimisation. Misc thoughts: - I'm not familiar with the LABS problem, but the LABS benchmark page is interesting & compares against Gurobi. I'd be curious to see how an existing commercial non-mip approximate solver such as Hexaly (formerly LocalSolver) compares here. - the other two benchmarks aren't very c…

Does anyone use Hexaly for any serious work? If so, why? There seem to be many better alternatives out there.

Amazon has been quite vocal about using Hexaly.

Re: Optimization Solver as a Service

#16

Post by whatever1 » Sun, Jul 12, 2026, 5:23 AM UTC

luiwammus wrote: post #15

LPisGood wrote: post #11

Earlier quoted context omitted.

Does anyone use Hexaly for any serious work? If so, why? There seem to be many better alternatives out there.

Amazon has been quite vocal about using Hexaly.

All vendors just need 1 engineer in a BigCorp to have used their software to claim "Trusted by BigCorpName"

Re: Optimization Solver as a Service

#17

Post by luiwammus » Sun, Jul 12, 2026, 5:25 AM UTC

LPisGood wrote: post #11

shoo wrote: post #8

I'm not a potential customer for this, but i have worked on a few commercial projects involving combinatorial optimisation. Misc thoughts: - I'm not familiar with the LABS problem, but the LABS benchmark page is interesting & compares against Gurobi. I'd be curious to see how an existing commercial non-mip approximate solver such as Hexaly (formerly LocalSolver) compares here. - the other two benchmarks aren't very c…

Does anyone use Hexaly for any serious work? If so, why? There seem to be many better alternatives out there.

The main reason why companies might prefer Hexaly is their emphasis on quickly finding high Quality feasible primal solutions.

Re: Optimization Solver as a Service

#18

Post by tirutiru » Sun, Jul 12, 2026, 5:27 AM UTC

LPisGood wrote: post #11

shoo wrote: post #8

I'm not a potential customer for this, but i have worked on a few commercial projects involving combinatorial optimisation. Misc thoughts: - I'm not familiar with the LABS problem, but the LABS benchmark page is interesting & compares against Gurobi. I'd be curious to see how an existing commercial non-mip approximate solver such as Hexaly (formerly LocalSolver) compares here. - the other two benchmarks aren't very c…

Does anyone use Hexaly for any serious work? If so, why? There seem to be many better alternatives out there.

I'm curious too. And what are the far better alternatives in your opinion?

Hexaly claims to go far beyond MIP. Amazon uses it for packing VMs into servers. This video by one of their research scientists was widely circulated at the time [1].

I work on combinatorial optimization too but a specific problem so we write the heuristics from scratch. Seems exact solvers are doing a lot more these days?

[1] https://www.youtube.com/watch?v=GIh6d3rb0_4

Re: Optimization Solver as a Service

#19

Post by deanalyzer » Sun, Jul 12, 2026, 5:57 AM UTC

This could be interesting, but it badly needs systematic benchmarking results. It is not difficult to get Claude Code or Codex to install and run a solver locally, so the tool’s current value proposition is fairly muddled.

If there were evidence that it offered better performance, I might consider running larger workloads on it.

Re: Optimization Solver as a Service

#20

Post by ge0ffrey » Sun, Jul 12, 2026, 6:29 AM UTC

Sounds similar to Timefold Platform: app.timefold.ai

That's our Solver as a Service for scheduling problems (vehicle routing problem, shift scheduling, job scheduling, etc). It runs scheduling problems implemented with our open source solver: solver.timefold.ai

But this post is such a service for formula problems instead (think master capacity planning, portfolio optimization, etc), due to the choice of MILP solvers underneath. Similar to NextMv, Neos, etc.