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cuopt-numerical-optimization-api-cli

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

1.0k|218|Updated Apr 8, 2025
Search Tags:#optimization#command-line#milp#mps#qp#cuopt#solver-tuning
One-click install
npx skills add https://github.com/NVIDIA/cuopt --skill cuopt-numerical-optimization-api-cli-nvidia
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cuopt-numerical-optimization-api-cli
Source: https://github.com/NVIDIA/cuopt/tree/main/skills/cuopt-numerical-optimization-api-cli
Command: npx skills add https://github.com/NVIDIA/cuopt --skill cuopt-numerical-optimization-api-cli-nvidia

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 problems by running NVIDIA cuOpt from the command line using MPS input files.

Core Features & Use Cases

  • MPS-driven optimization workflow (CLI only): Use cuopt_cli with the standard MPS section ordering to supply objective, constraints, and bounds.
  • LP and MILP support: Solve models with continuous and (optionally) integer variables using MPS integer markers.
  • QP support (beta): Solve quadratic objectives using the MPS quadratic-objective extension with the required restrictions.

Quick Start

Run the CLI on an MPS file by executing: cuopt_cli problem.mps with the time limit set using the appropriate flag.

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 MPS optimization problems from the command line?▼

Solving MPS optimization problems from the command line involves running `cuopt_cli problem.mps` with flags for time limits and tolerances. It handles LP, MILP, and beta QP models directly from the terminal.

Does cuopt_cli support mixed-integer linear programming models?▼

cuopt_cli supports mixed-integer linear programming by utilizing MPS integer markers. You define integer variables within your MPS file using MARKER INTORG and INTEND sections to successfully solve MILP models.

What are the MPS section ordering requirements for cuopt_cli?▼

Strict MPS section ordering is required for cuopt_cli, including optional BOUNDS and mandatory ENDATA sections. Structuring objective, constraints, and bounds correctly ensures the file parses without errors.

Can I solve quadratic programming problems using an MPS file?▼

Solving quadratic programming problems using an MPS file is supported in beta via the quadratic-objective extension. You must enforce QP-specific constraints and required restrictions for the solver to process the objective.

How do I tune solver settings like time limits for LP and MILP models?▼

Tuning solver settings for LP and MILP models involves using appropriate command-line flags when executing `cuopt_cli`. Adjust parameters like time limits and tolerances to control the optimization execution workflow.

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