cuopt-numerical-optimization-api

# cuOpt Numerical Optimization API Model and solve LP, MILP, and QP problems using NVIDIA cuOpt's GPU-accelerated solver. ## Interface Selection Choose the reference for the user's interface: | Interface | When to use | Reference | |-----------|-------------|-----------| | **Python** | User is writing Python code | [references/python_api.md](references/python_api.md) | | **C / C++** | User is embedding in a C/C++ application | [references/c_api.md](references/c_api.md) | | **CLI** | User is solving from MPS files on the command line | [references/cli_api.md](references/cli_api.md) | If the interface is not yet clear, ask before writing any code. **Already using a modeling language?** cuOpt also works as a solver backend for third-party modeling tools — **AMPL, GAMS / GAMSPy, PuLP, JuMP, Pyomo, and CVXPY** — with near-zero code changes (point the model's solver at cuOpt). CVXPY additionally covers convex QP and, in beta, QCQP / SOCP. Prefer this when the user already has a model in one of these tools rather than porting it to the cuOpt API. See [Third-Party Modeling Languages](https://docs.nvidia.com/cuopt/user-guide/latest/thirdparty_modeling_languages/index.html). ## Choosing LP vs MILP vs QP **Decide from the objective and variables:** | If the objective is... | And variables are... | Use | |---|---|---| | Linear (sum of `c_i * x_i`) | All continuous | **LP** | | Linear | Some integer or binary | **MILP** | | Has squared (`x*x`) or cross (`x*y`) terms | Continuous ...