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cuopt-numerical-optimization-api-cli

Solve LP, MILP, and beta QP problems from MPS files via cuopt_cli.

Updated May 23, 2026
Search Tags:#optimization#linear programming#command line#MPS#quadratic programming#mixed integer#cuopt_cli
One-click install
npx skills add https://github.com/yo-steven/skills-exploration-20260522 --skill cuopt-numerical-optimization-api-cli
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cuopt-numerical-optimization-api-cli
Source: https://github.com/yo-steven/skills-exploration-20260522/tree/main/skills/cuopt/cuopt-numerical-optimization-api-cli
Command: npx skills add https://github.com/yo-steven/skills-exploration-20260522 --skill cuopt-numerical-optimization-api-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill helps you solve linear, mixed-integer, and quadratic optimization models by turning MPS files into computed solutions using NVIDIA cuOpt through a command-line workflow.

Core Features & Use Cases

  • CLI-only MPS solving: Runs cuOpt using the cuopt_cli command with the same overall workflow for LP, MILP, and QP (beta).
  • Model validation guidance: Emphasizes confirming formulation details like variable types, constraints, and objective before running.
  • QP support for quadratic objectives (beta): Uses the MPS quadratic-objective extension with clear restrictions (minimize only; continuous variables only when using quadratic objectives).
  • Useful sample MPS assets: Provides runnable example problems (LP, MILP) for quick verification of your setup.

Quick Start

Run cuopt_cli on your MPS file to solve an LP or MILP, for example: cuopt_cli problem.mps --time-limit 120.

Frequently Asked Questions about cuopt-numerical-optimization-api-cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I solve a linear programming model from an MPS file using a command line interface?▼

Solve linear programming models from MPS files by running the cuopt_cli command, which processes LP, MILP, and QP formulations directly from your terminal to compute solutions.

What are the restrictions for solving quadratic programming problems with MPS files?▼

Quadratic programming problems using MPS files require minimize-only objectives and continuous variables. The solver enforces these QP-specific rules when processing the quadratic-objective extension.

Can I configure solver tolerances and iteration limits for mixed integer programming via CLI?▼

Configure tolerances, presolve settings, iteration limits, and method selection for mixed integer programming by passing configuration parameters to the cuopt_cli command during execution.

What MPS section order is required to successfully solve optimization models?▼

MPS files must follow a strict section order: NAME, ROWS, COLUMNS, RHS, optional BOUNDS, and ENDATA. Correct integer marker usage is also required for MILP formulations to solve properly.

Does the solver support sample MPS files for verifying my optimization setup?▼

The solver includes runnable example MPS assets for both LP and MILP problems, allowing you to quickly verify your command line setup and configuration before processing your own models.

Why is my quadratic programming model failing to solve from the MPS file?▼

Quadratic programming models fail if the MPS file violates QP restrictions, such as including integer variables or using a maximize objective. Ensure your formulation is minimize-only with continuous variables.

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