MathOpt is an API for modeling and solving optimization problems from C++ and Python. The MathOpt service is an experimental set of methods within the OR API that lets you to solve mathematical optimization problems remotely using the endpoint:
https://optimization.googleapis.com/v1/mathopt:solveMathOptModel
MathOpt Features
MathOpt models can contain:
- Integer or continuous variables
- Linear or quadratic constraints
- Linear or quadratic objectives
Models are defined independently of any solver and solvers can be swapped
interchangeably. The following solvers are supported in the SolveMathOptModel:
The MathOpt service supports most the features of MathOpt when solving a model, including:
- Duality
- Primal and dual rays
- Suboptimal primal and dual solutions
- Warm starts (by solution or basis)
- Detailed termination reason
- Branching priority
- Many solver independent parameters
Callbacks, incrementalism, and interruption are not yet supported. The MathOpt service will support these features in the future using a richer communication protocol.
Setup and Installation
To use MathOpt's remote solve capabilities, you need an API key that can be obtained following the setup guide. MathOpt provides client libraries in C++ and Python, which are available as part of OR-Tools since release 9.9.
You can reach out to or-mathopt-service+support@google.com should you have questions related to the MathOpt service.