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.
ソース情報
- リポジトリ
- autohandai/community-skills
- ソースの最終更新活動
- 2026年6月30日 03:25
- 検出された SKILL.md の言語
- 英語
- スター
- 11
- フォーク
- 3
インストール方法
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
ソースファイルを確認
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
ファイルエクスプローラー
11 ファイルSKILL.md を表示中
SKILL.md
ソースの指示 · 読み取り専用プレビュー- 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.
GitHubで見る