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google
or-tools
C++2015–2025
google / or-tools

or-tools

Google's Operations Research tools:

Science & Engineering
Explore on GitHubRead Hacker News discussions
13Distinct people
13Mentions
0Explicit recommenders
14.4KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Google's Operations Research tools:

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year13 dated mentions

Observed mentions: 2015-05-09 00:06:04 UTC to 2025-06-30 02:49:47 UTC.

0122015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20152016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC202
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC211
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC211
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC211
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC202
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

13 sources
hakank·Sep 12, 2022
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
Read the rest
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). """
In Constraint Programming
danpat·Nov 26, 2019
If you want to get fancy with your meal planning, you can use a constraint solver like Google's or-tools to figure out what recipes to cook to meet nutritional (and other) goals semi-optimally: Example code: https://github.com/google/or-tools/blob/stable/examples/pyth... which solves the Stigler Diet problem: https://en.wikipedia.org/wiki/Stigler_diet The combinatoric difficulty of optimal nutrition planning is not something I see brought up very often, and I find that fascinating in its own right. It's harder than it looks, and I feel many people don't understand why.
In Calorie Counting × Meal Planning
glennon·Jun 5, 2015
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/geis
Read the rest
berger_... 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).
In Show HN: Valhalla, an open source routing engine

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