Software:OR-Tools

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Short description: Open source software suite by Google


OR-Tools
OR-Tools Logo.png
Original author(s)Laurent Perron
Developer(s)Google Optimization team[1]
Initial releaseSeptember 15, 2010; 13 years ago (2010-09-15)
Stable release
v9.4.1874[2] / August 12, 2022; 20 months ago (2022-08-12)
Repositorygithub.com/google/or-tools
Written inC++
Operating systemLinux, macOS, Microsoft Windows
TypeLibrary
LicenseApache License 2.0
Websitedevelopers.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][4]

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.[5]

History

OR-Tools was created by Laurent Perron in 2011.[6]

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

The CP-SAT solver[7] bundled with OR-Tools won a total of eleven gold medals between 2018 and 2020 in the MiniZinc Challenge,[8] an international constraint programming competition.

Features

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

OR-Tools supports a wide range of problem types,[13][3] among them:

It supports the FlatZinc modeling language.[18]

See also

References

  1. 1.0 1.1 "Sudoku, Linear Optimization, and the Ten Cent Diet". https://ai.googleblog.com/2014/09/sudoku-linear-optimization-and-ten-cent.html. 
  2. "Release v9.4". https://github.com/google/or-tools/releases/tag/v9.4. 
  3. 3.0 3.1 "Google OR-Tools a guide". February 24, 2019. https://medium.com/google-or-tools/google-or-tools-a-guide-39f439a5cd0f. 
  4. "We help you implement OR-tools technology". https://www.solvice.io/technology/or-tools. 
  5. "LICENSE-2.0.txt". https://github.com/google/or-tools/blob/stable/LICENSE-2.0.txt. 
  6. Perron, Laurent (2011-07-01). "Operations Research and Constraint Programming at Google". Lee J. (Eds) Principles and Practice of Constraint Programming – CP 2011. Lecture Notes in Computer Science 6876: 2. doi:10.1007/978-3-642-23786-7_2. ISBN 978-3-642-23786-7. 
  7. 7.0 7.1 "How the CP-SAT solver works". April 25, 2020. https://www.xiang.dev/explaining-cp-sat/. 
  8. "The MiniZinc Challenge". https://www.minizinc.org/challenge.html. 
  9. "Homebrew package". https://formulae.brew.sh/formula/or-tools. 
  10. "com.google.ortools:ortools-java". https://mvnrepository.com/artifact/com.google.ortools/ortools-java. 
  11. "Google.OrTools". https://www.nuget.org/packages/Google.OrTools/. 
  12. "ortools". https://pypi.org/project/ortools/. 
  13. "OR-Tools introduction". https://developers.google.com/optimization/introduction/overview. 
  14. 14.0 14.1 "Application of Google OR-Tools". https://www.kaggle.com/jpmiller/application-of-google-or-tools. 
  15. "Google OR-Tools. Business value and potential". https://freshcodeit.com/google-or-tools. 
  16. Louat, Christophe (2009). Etude et mise en œuvre de stratégies de coupes efficaces pour des problèmes entiers mixtes 0-1 (PhD). 1. Université de Versailles Saint-Quentin-en-Yvelines. p. 144.
  17. "Routing use case". https://activimetrics.com/blog/ortools/multiday_tsp. 
  18. "Software with FlatZinc implementations". https://www.minizinc.org/software.html#flatzinc. 

Bibliography

External links