GLOP (the Google Linear Optimization Package) is Google's open source linear programming solver, created by Google's Operations Research Team. It is written in C++ and was released to the public as part of Google's OR-Tools software suite in 2014.[1]

GLOP uses a revised primal-dual simplex algorithm optimized for sparse matrices. It uses Markowitz pivoting to reduce matrix fill-in, steepest-edge pricing to avoid degenerate pivots, and an LU decomposition tailored for sparse matrices.

Inside Google, GLOP is used to stabilize YouTube videos[2] and outside Google, it has been used to perform fast linear relaxations for reinforcement learning.[3]

References

  1. ↑ "Sudoku, Linear Optimization, and the Ten Cent Diet".
  2. ↑ "Sudoku, Linear Optimization, and the Ten Cent Diet".
  3. ↑ "A structured prediction approach for generalization in cooperative multi-agent reinforcement learning".
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