Skip to main content

nvidia-cuopt-numerical-optimization-api-cli

LP, MILP, and QP (beta) with cuOpt — CLI only (MPS files, cuopt_cli). Use when the user is solving LP, MILP, or QP from MPS via command line.

Source facts

Repository
autohandai/community-skills
Last source activity
June 30, 2026 at 03:25
Detected SKILL.md language
English
Stars
11
Forks
3

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

File Explorer
11 files

Showing SKILL.md

SKILL.md
Source instructions · Read-only preview
name
nvidia-cuopt-numerical-optimization-api-cli
description
LP, MILP, and QP (beta) with cuOpt — CLI only (MPS files, cuopt_cli). Use when the user is solving LP, MILP, or QP from MPS via command line.
license
Apache-2.0 AND CC-BY-4.0
metadata
{"version":"26.08.00","author":"NVIDIA"}
# cuOpt Numerical Optimization — CLI Solve LP, MILP, and QP problems from MPS files via `cuopt_cli`. The same command, options, and MPS workflow apply across all three; QP uses the standard MPS quadratic-objective extension. Confirm problem type and formulation (variables, objective, constraints, variable types) before coding. This skill is **CLI only** (MPS input). ## Basic usage ```bash # Solve LP or MILP from MPS file cuopt_cli problem.mps # With options cuopt_cli problem.mps --time-limit 120 --mip-relative-tolerance 0.01 ``` ## Common options ```bash cuopt_cli --help # Time limit (seconds) cuopt_cli problem.mps --time-limit 120 # MIP gap tolerance (stop when within X% of optimal) cuopt_cli problem.mps --mip-relative-tolerance 0.001 # MIP absolute tolerance cuopt_cli problem.mps --mip-absolute-tolerance 0.0001 # Presolve, iteration limit, method cuopt_cli problem.mps --presolve --iteration-limit 10000 --method 1 ``` ## MPS format (required sections, in order) 1. **NAME** — problem name 2. **ROWS** — N (objective), L/G/E (constraints) 3. **COLUMNS** — variable names, row names, coefficients 4. **RHS** — right-hand side values 5. **BOUNDS** (optional) — LO, UP, FX, BV, LI, UI 6. **ENDATA** Integer variables: use `'MARKER' 'INTORG'` before and `'MARKER' 'INTEND'` after the integer columns. ## QP via CLI (beta) Quadratic objectives extend the standard MPS workflow — same `cuopt_cli` command, same options. Check `cuopt_cli --help` for QP-specific flags and the repo docs at `docs/cuopt/source/cuopt-cli/` for the quadratic-objective MPS format. **QP rules:** - **MINIMIZE only.** For maximization, negate the objective coefficients (and Q entries) in the MPS file. - **Continuous variables only** — do not mix integer markers with quadratic objectives. ## Troubleshooting - **Failed to parse MPS** — Check ENDATA, section order (NAME, ROWS, COLUMNS, RHS, [BOUNDS], ENDATA), integer markers. - **Infeasible** — Check constraint directions (L/G/E) and RHS values. ## Examples - [assets/README.md](assets/README.md) — Build/run for sample MPS files - [lp_simple](assets/lp_simple/) — Minimal LP (PROD_X, PROD_Y, two constraints) - [lp_production](assets/lp_production/) — Production planning: chairs + tables, wood/labor - [milp_facility](assets/milp_facility/) — Facility location with binary open/close ## Getting the CLI CLI is included with the Python package (`cuopt`). Install via pip or conda; then run `cuopt_cli --help` to verify.
View on GitHub