What does HackerNews think of or-tools?

Google's Operations Research tools:

Language: C++

Yes, OR-tools has a lot of solvers. The solver I talked about is the CP-SAT solver. It's described (https://www.minizinc.org/challenge2022/description_or-tools_... ) as:

""" CP-SAT is a discrete optimization solver built on top of a SAT engine. It is available within the OR-Tools open-source repository (website: https://developers.google.com/optimization, github repository: https://github.com/google/or-tools). It has won multiple gold medals at the MiniZinc challenge (https://www.minizinc.org/challenge.html) since its debut in 2017.

The CP-SAT solver is architectured around five components: The base layer is a clause learning SAT solver. Above the SAT layer sits a Constraint Programming (CP) module with Boolean, integer and interval variables, and standard integer, scheduling and routing constraints. Alongside the CP solver, a simplex provides a global linear relaxation. Its integration with the CP and SAT layers enable the CP-SAT solver to solve MIP problems with the same techniques as (commercial) MIP solvers: relaxation, cuts, heuristics and duality based techniques. Both the CP and MIP modules rely on a unified protobuf representation of the model that can serve as a file format, as well as an intermediate representation of the model during all phases of the solve (input format, presolved model, LNS fragment). On top, the search layer implements a robust information-sharing portfolio of specialized workers that offers both good and fast solutions, and superior optimality proving capabilities.

This work was presented at the CPAIOR 2020 masterclass. The recording is available on youtube (https://www.youtube.com/watch?v=lmy1ddn4cyw). """

We have an in house system built from ground up in Python and use ortools (https://github.com/google/or-tools) to power the core of the algorithms.
For speedy street routing, the Open Source Routing Machine: http://project-osrm.org/ Like Google's proprietary routing engine, it leverages the scale of local and regional travel (via contraction hierarchies, arterial travel is suited for precomputed cacheing); result: the system can be tuned to give near instantaneous results. OSRM had been led by Dennis Luxen of Mapbox, though he just moved to Apple. The OP (Mapzen's Valhalla) appears to have a similar approach as OSRM. Good libraries for other scenarios exist; e.g., cycling and multimodal planning -- see: http://wiki.openstreetmap.org/wiki/Routing and OpenTripPlanner https://github.com/opentripplanner/OpenTripPlanner

There's an academic Thesis on the principles of contraction hierarchies that is worth a look if you're in this space. http://algo2.iti.kit.edu/documents/routeplanning/geisberger_... My favorite is actually a Master's thesis that steps through the process of using contraction hierarchies to build a routing engine (MoNav) on OpenStreetMap data. https://code.google.com/p/monav/downloads/detail?name=thesis...

For nuanced or complex problems, set up your objectives and constraints against a good solver: http://en.wikipedia.org/wiki/List_of_optimization_software I'm partial to Google's OR Tools https://github.com/google/or-tools (Apache License).

Reddit has a few subreddits for operations research. You may have better luck there: https://www.reddit.com/r/msor/ , https://www.reddit.com/r/sysor/.

Also google has some famous operation research tools: https://github.com/google/or-tools .

I think operations research is a very broad topic. There is probably heavy overlap in managing large graphs of information as well.