cuopt-lp-milp-api-c

To solve MILP problems in C/C++, define your model with CSR constraint matrices, variable bounds, and types, then call cuOpt's C API. This approach embeds optimization directly without external solver processes.

A CSR (Compressed Sparse Row) constraint matrix efficiently defines linear programming constraints by storing non-zero values and indices. cuOpt's C API uses this format to handle large, sparse LP models in C/C++ applications.

Yes, you can solve MPS files using the cuOpt C API. The mps_solver example demonstrates how to load standard MPS problem files and configure the solver for execution within C/C++ deployments.

Yes, embedding cuOpt requires including specific C API headers like cuopt/linear_programming/cuopt_c.h and constants.h. These provide the necessary function declarations and constants for problem formulation.

Yes, cuOpt provides ready-to-run examples like lp_basic, milp_basic, and mps_solver. These samples demonstrate everything from basic formulation to production-grade solver configuration for C/C++ integration.

Using a C API for linear programming requires manual CSR constraint matrix construction and explicit memory management compared to high-level interfaces. However, it provides tighter integration and lower overhead for embedded deployments.