cuopt-numerical-optimization-api-python
CommunitySolve LP, MILP, and QP with cuOpt Python.
Software Engineering#optimization#linear programming#python api#quadratic programming#cuopt#mixed integer programming#gpu solver
Authoryo-steven
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps you model and solve Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Quadratic Programming (QP, beta) problems using NVIDIA cuOpt’s GPU-accelerated Python API.
Core Features & Use Cases
- Unified Python API for LP, MILP, and QP via shared classes and a common solve flow.
- Objective and variable selection guidance to choose LP vs MILP vs QP based on linear/quadratic structure and continuous vs integer variables.
- Reference models in assets for common patterns like duals, warmstarts (LP), production planning (MILP), portfolio QP, and least-squares QP.
Quick Start
Ask for an optimization model solution for your scheduling, resource allocation, facility location, production planning, portfolio optimization, or least-squares problem in cuOpt Python.
Dependency Matrix
Required Modules
None requiredComponents
assetsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: cuopt-numerical-optimization-api-python Download link: https://github.com/yo-steven/skills-exploration-20260522/archive/main.zip#cuopt-numerical-optimization-api-python Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 471,000+ vetted skills library on demand.