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cuopt-numerical-optimization-api-cli

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

Updated Apr 16, 2026
Search Tags:#optimization#cli#milp#linear-programming#mps#qp#cuopt
One-click install
npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill cuopt-numerical-optimization-api-cli-sayalinvidia
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cuopt-numerical-optimization-api-cli
Source: https://github.com/sayalinvidia/sayali-skills-test/tree/main/skills/cuopt-numerical-optimization-api-cli
Command: npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill cuopt-numerical-optimization-api-cli-sayalinvidia

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

cuOpt CLI enables solving LP, MILP, and QP problems directly from MPS files via the cuopt_cli command line tool, reducing manual modeling and scripting boilerplate.

Core Features & Use Cases

  • CLI-only workflow for MPS-based optimization across LP, MILP, and QP (including QP via MPS) with consistent parameters and workflow.
  • Supports common options such as time-limit, mip-relative-tolerance, mip-absolute-tolerance, presolve, iteration-limit, and method to control accuracy and performance.
  • Use Case: developers and data scientists solve optimization problems from MPS inputs to inform decisions in operations research and planning tasks.

Quick Start

Run cuopt_cli on an MPS file to solve your optimization problem from the terminal.

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 problem from an MPS file using the command line?▼

To solve a linear programming problem from an MPS file, run the cuopt_cli command directly in your terminal, which processes the MPS input and returns the optimization results without requiring manual scripting boilerplate.

Can I solve mixed-integer linear programming problems using cuOpt CLI?▼

Yes, cuOpt CLI solves mixed-integer linear programming (MILP) problems directly from MPS files, recognizing integer markers like INTORG and INTEND to properly handle integer variable constraints.

What optimization options are available when solving MPS files from the terminal?▼

When solving MPS files from the terminal, you can specify options including time-limit, mip-relative-tolerance, mip-absolute-tolerance, presolve, iteration-limit, and method to control solver accuracy and performance.

Does cuOpt CLI support quadratic programming problems in MPS format?▼

Yes, cuOpt CLI supports solving quadratic programming (QP) problems directly from MPS files, providing a consistent CLI workflow for LP, MILP, and QP optimization tasks across operations research projects.

How do I control the solver time limit for MILP problems in a CLI workflow?▼

To control the solver time limit for MILP problems in a CLI workflow, pass the --time-limit parameter to cuopt_cli, constraining the optimization duration to fit your operational planning requirements.

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