OR-Tools

OR-Tools
Original author(s)	Laurent Perron
Developer(s)	Google Optimization team
Initial release	September 15, 2010; 14 years ago
Stable release	v9.9.3963 / March 7, 2024; 8 months ago
Repository	github.com/google/or-tools
Written in	C++
Operating system	Linux, macOS, Microsoft Windows
Type	Library
License	Apache License 2.0
Website	developers.google.com/optimization/

Google OR-Tools is a free and open-source software suite developed by Google for solving linear programming (LP), mixed integer programming (MIP), constraint programming (CP), vehicle routing (VRP), and related optimization problems.^[3]

OR-Tools is a set of components written in C++ but provides wrappers for Java, .NET and Python.

It is distributed under the Apache License 2.0.^[4]

History

OR-Tools was created by Laurent Perron in 2011.^[5]

In 2014, Google's open source linear programming solver, GLOP, was released as part of OR-Tools.^[1]

The CP-SAT solver^[6] bundled with OR-Tools has been consistently winning gold medals in the MiniZinc Challenge,^[7] an international constraint programming competition.

Features

The OR-Tools supports a variety of programming languages, including:

Object-oriented interfaces for C++^[8]
A Java wrapper package^[9]
A .NET and .NET Framework wrapper package^[10]
A Python wrapper package^[11]

OR-Tools supports a wide range of problem types,^[12]^[3] among them:

It supports the FlatZinc modeling language.^[16]

References

^ ^a ^b "Sudoku, Linear Optimization, and the Ten Cent Diet". ai.googleblog.com.
^ "Release v9.9". github.com.
^ ^a ^b "Google OR-Tools a guide". medium.com. February 24, 2019.
^ "LICENSE-2.0.txt". github.com.
^ Perron, Laurent (July 1, 2011). "Operations Research and Constraint Programming at Google". Lee J. (Eds) Principles and Practice of Constraint Programming – CP 2011. Lecture Notes in Computer Science. Vol. 6876. p. 2. doi:10.1007/978-3-642-23786-7_2. ISBN 978-3-642-23786-7. S2CID 38166333.
^ ^a ^b "How the CP-SAT solver works". xiang.dev. April 25, 2020.
^ "The MiniZinc Challenge". minizinc.org.
^ "Homebrew package". formulae.brew.sh.
^ "com.google.ortools:ortools-java". mvnrepository.com.
^ "Google.OrTools". nuget.org.
^ "ortools". pypi.org.
^ "OR-Tools introduction". Google Developers.
^ ^a ^b "Application of Google OR-Tools". kaggle.com.
^ Louat, Christophe (2009). Etude et mise en œuvre de stratégies de coupes efficaces pour des problèmes entiers mixtes 0-1 (PhD). Vol. 1. Université de Versailles Saint-Quentin-en-Yvelines. p. 144.
^ "Routing use case". activimetrics.com.
^ "Software with FlatZinc implementations". minizinc.org.

Bibliography

Kruk, Serge (February 26, 2018). Practical Python AI Projects: Mathematical Models of Optimization Problems with Google OR-Tools (1st ed.). O'Reilly Media. ISBN 9781484234235.
Da Col, Giacomo; Teppan, Eric C. (2019). "Google vs IBM: A Constraint Solving Challenge on the Job-Shop Scheduling Problem". Electronic Proceedings in Theoretical Computer Science. 306. Open Publishing Association: 259–265. doi:10.4204/eptcs.306.30. ISSN 2075-2180. S2CID 202660711.
Li, Mengyun; Chow, Joseph (April 2021). "School Bus Routing Problem with a Mixed Ride, Mixed Load, and Heterogeneous Fleet". Transportation Research Record Journal of the Transportation Research Board. 2675 (7): 467–479. doi:10.1177/03611981211016860. S2CID 237618523.

External links

[glop-1] "Sudoku, Linear Optimization, and the Ten Cent Diet". ai.googleblog.com.

[2] "Release v9.9". github.com.

[medium-3] "Google OR-Tools a guide". medium.com. February 24, 2019.

[license-4] "LICENSE-2.0.txt". github.com.

[5] Perron, Laurent (July 1, 2011). "Operations Research and Constraint Programming at Google". Lee J. (Eds) Principles and Practice of Constraint Programming – CP 2011. Lecture Notes in Computer Science. Vol. 6876. p. 2. doi:10.1007/978-3-642-23786-7_2. ISBN 978-3-642-23786-7. S2CID 38166333.

[xiang-6] "How the CP-SAT solver works". xiang.dev. April 25, 2020.

[7] "The MiniZinc Challenge". minizinc.org.

[8] "Homebrew package". formulae.brew.sh.

[9] "com.google.ortools:ortools-java". mvnrepository.com.

[10] "Google.OrTools". nuget.org.

[11] "ortools". pypi.org.

[12] "OR-Tools introduction". Google Developers.

[kaggle-13] "Application of Google OR-Tools". kaggle.com.

[14] Louat, Christophe (2009). Etude et mise en œuvre de stratégies de coupes efficaces pour des problèmes entiers mixtes 0-1 (PhD). Vol. 1. Université de Versailles Saint-Quentin-en-Yvelines. p. 144.

[15] "Routing use case". activimetrics.com.

[flatzinc-16] "Software with FlatZinc implementations". minizinc.org.

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