cuopt-numerical-optimization-api-c

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LP, MILP, and QP (beta) with cuOpt — C API only. Use when the user is embedding LP, MILP, or QP in C/C++.

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Added on2026-05-22

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cuOpt Numerical Optimization — C API

Solve LP, MILP, and QP problems via the cuOpt C API. The same library, headers, build pattern, and core calls (

cuOptCreate*Problem

,

cuOptSolve

,

cuOptGetObjectiveValue

) apply across all three; QP extends the API with quadratic-objective creation calls.

Confirm problem type and formulation (variables, objective, constraints, variable types) before coding.

This skill is C only.

Quick Reference: C API

c

#include <cuopt/linear_programming/cuopt_c.h>

// CSR format for constraints
cuopt_int_t row_offsets[] = {0, 2, 4};
cuopt_int_t col_indices[] = {0, 1, 0, 1};
cuopt_float_t values[] = {2.0, 3.0, 4.0, 2.0};
char var_types[] = {CUOPT_CONTINUOUS, CUOPT_INTEGER};

cuOptCreateRangedProblem(
    num_constraints, num_variables, CUOPT_MINIMIZE,
    0.0, objective_coefficients,
    row_offsets, col_indices, values,
    constraint_lower, constraint_upper,
    var_lower, var_upper, var_types,
    &problem
);
cuOptSolve(problem, settings, &solution);
cuOptGetObjectiveValue(solution, &obj_value);

QP via C API (beta)

QP uses the same library, include/lib paths, and build pattern as LP/MILP — only the problem-creation call differs (it accepts a quadratic objective). See the cuOpt C headers (

cpp/include/cuopt/linear_programming/

) for the QP-specific creation/solve calls and the repo docs at

docs/cuopt/source/cuopt-c/lp-qp-milp/

for end-to-end QP examples.

QP rules:

MINIMIZE only (
```
CUOPT_MINIMIZE
```
). To maximize
```
f(x)
```
, negate objective coefficients and Q entries.
Continuous variables only — set
```
CUOPT_CONTINUOUS
```
for every variable; integer QP is not supported.
Q should be PSD for a convex problem.

Debugging (MPS / C)

MPS parsing: Required sections in order: NAME, ROWS, COLUMNS, RHS, (optional) BOUNDS, ENDATA. Integer markers:

'MARKER'

,

'INTORG'

,

'INTEND'

.

OOM or slow: Check problem size (variables, constraints); use sparse matrix; set time limit and gap tolerance.

Examples

examples.md — LP/MILP with build instructions
assets/README.md — Build commands for all reference code below
lp_basic — Simple LP: create problem, solve, get solution
lp_duals — Dual values and reduced costs
lp_warmstart — PDLP warmstart (see README)
milp_basic — Simple MILP with integer variable
milp_production_planning — Production planning with resource constraints
mps_solver — Solve from MPS file via
```
cuOptReadProblem
```

For CLI (MPS files), use

cuopt_cli

and product docs.

Escalate

For contribution or build-from-source, use product or repo documentation.